Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

2015/02/11 by Sergey Ioffe, Christian Szegedy, Ioffe, Sergey +1 · 3 voices · 24,402 citations
Computer Science · Mathematics · #Artificial intelligence #Computer science #Covariate #Domain Adaptation and Few-Shot Learning #Econometrics #Geography #Machine Learning and ELM #Mathematics #Neural Networks and Applications #Normalization (sociology) #Statistics #Training (meteorology) #cs.LG

paper · pdf · doi:10.48550/arxiv.1502.03167

published in arXiv (Cornell University) (Cornell University)

openalex publication_date 2015/02/11 · arxiv created 2015/03/02 · arxiv updated 2015/03/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

Training Deep Neural Networks is complicated by the fact that the distribution of each layer's inputs changes during training, as the parameters of the previous layers change. This slows down the training by requiring lower learning rates and careful parameter initialization, and makes it notoriously hard to train models with saturating nonlinearities. We refer to this phenomenon as internal covariate shift, and address the problem by normalizing layer inputs. Our method draws its strength from making normalization a part of the model architecture and performing the normalization for each training mini-batch. Batch Normalization allows us to use much higher learning rates and be less careful about initialization. It also acts as a regularizer, in some cases eliminating the need for Dropout. Applied to a state-of-the-art image classification model, Batch Normalization achieves the same accuracy with 14 times fewer training steps, and beats the original model by a significant margin. Using an ensemble of batch-normalized networks, we improve upon the best published result on ImageNet classification: reaching 4.9% top-5 validation error (and 4.8% test error), exceeding the accuracy of human raters.

Citations

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• Pruning Self-attentions into Convolutional Layers in Single Path
• Random Erasing Data Augmentation
• "Tom" pet robot applied to urban autism
• Beyond Random: Automatic Inner-loop Optimization in Dataset Distillation
• How does the optimizer implicitly bias the model merging loss landscape?
• Noise or Signal? Deconstructing Contradictions and An Adaptive Remedy for Reversible Normalization in Time Series Forecasting
• Tensor Regression Networks
• Data-Driven Filtering of the Spherical Harmonics Method
• Meta-Learning with Adaptive Hyperparameters
• Interactive Training: Feedback-Driven Neural Network Optimization
• Understanding Negative Samples in Instance Discriminative Self-supervised Representation Learning
• Discretized Quadratic Integrate-and-Fire Neuron Model for Deep Spiking Neural Networks
• An Efficient Approach to Informative Feature Extraction from Multimodal Data
• A Comprehensive Review of Deep Learning-based Single Image Super-resolution
• FHEON: A Configurable Framework for Developing Privacy-Preserving Neural Networks Using Homomorphic Encryption
• Deep Learning for Image Super-Resolution: A Survey
• Image Enhancement Based on Pigment Representation
• On residual network depth
• On the Benefits of Weight Normalization for Overparameterized Matrix Sensing
• Momentum Contrast for Unsupervised Visual Representation Learning
• Digital Passport: A Novel Technological Strategy for Intellectual Property Protection of Convolutional Neural Networks
• [Extended version] Rethinking Deep Neural Network Ownership Verification: Embedding Passports to Defeat Ambiguity Attacks
• Randomized Matrix Sketching for Neural Network Training and Gradient Monitoring
• Generalized Parallel Scaling with Interdependent Generations
• High Fidelity Speech Synthesis with Adversarial Networks
• FedMuon: Federated Learning with Bias-corrected LMO-based Optimization
• Marginal Flow: a flexible and efficient framework for density estimation
• Reconcile Certified Robustness and Accuracy for DNN-based Smoothed Majority Vote Classifier
• ProbMed: A Probabilistic Framework for Medical Multimodal Binding
• Gamma-Based Statistical Modeling for Extended Target Detection in mmWave Automotive Radar
• AttentionViG: Cross-Attention-Based Dynamic Neighbor Aggregation in Vision GNNs
• XQC: Well-conditioned Optimization Accelerates Deep Reinforcement Learning
• U-SWIFT: A Unified Surface Wave Inversion Framework with Transformer via Normalization of Dispersion Curves
• Spatial-Functional awareness Transformer-based graph archetype contrastive learning for Decoding Visual Neural Representations from EEG
• Word-Level Emotional Expression Control in Zero-Shot Text-to-Speech Synthesis
• ScatterAD: Temporal-Topological Scattering Mechanism for Time Series Anomaly Detection
• Neural Visibility of Point Sets
• BALF: Budgeted Activation-Aware Low-Rank Factorization for Fine-Tuning-Free Model Compression
• Flexible Image Denoising with Multi-layer Conditional Feature Modulation
• ClimSat – A diffusion autoencoder model for climate-conditional satellite image editing
• Semantic Conditioned Dynamic Modulation for Temporal Sentence Grounding in Videos
• 2nd Place Solution to ECCV 2020 VIPriors Object Detection Challenge
• Weather GAN: Multi-Domain Weather Translation Using Generative Adversarial Networks
• Tent: Fully Test-time Adaptation by Entropy Minimization
• Understanding the Effects of Pre-Training for Object Detectors via Eigenspectrum
• Differentiable Sparsity via D-Gating: Simple and Versatile Structured Penalization
• CaRe-BN: Precise Moving Statistics for Stabilizing Spiking Neural Networks in Reinforcement Learning
• An Investigation of Batch Normalization in Off-Policy Actor-Critic Algorithms
• Deep Taxonomic Networks for Unsupervised Hierarchical Prototype Discovery
• Deep Optimization model for Screen Content Image Quality Assessment using Neural Networks
• Challenges in multi-task learning for fMRI-based diagnosis: Benefits for psychiatric conditions and CNVs would likely require thousands of patients
• Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs
• U-Net Training with Instance-Layer Normalization
• Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
• Deep Multi-Kernel Convolutional LSTM Networks and an Attention-Based Mechanism for Videos
• CProp: Adaptive Learning Rate Scaling from Past Gradient Conformity
• Beyond Gaussian Initializations: Signal Preserving Weight Initialization for Odd-Sigmoid Activations
• Training Deep Normalization-Free Spiking Neural Networks with Lateral Inhibition
• Automatic Analysis System of Calcaneus Radiograph: Rotation-Invariant Landmark Detection for Calcaneal Angle Measurement, Fracture Identification and Fracture Region Segmentation
• Shape-Informed Clustering of Multi-Dimensional Functional Data via Deep Functional Autoencoders
• Learning Unified Representation of 3D Gaussian Splatting
• EqCo: Equivalent Rules for Self-supervised Contrastive Learning
• Restructuring Batch Normalization to Accelerate CNN Training
• Multiple Attentional Pyramid Networks for Chinese Herbal Recognition
• Cross-Dialect Bird Species Recognition with Dialect-Calibrated Augmentation
• Johnson-Lindenstrauss Lemma Guided Network for Efficient 3D Medical Segmentation
• FastEnhancer: Speed-Optimized Streaming Neural Speech Enhancement
• Prompt-guided Disentangled Representation for Action Recognition
• POEM: Explore Unexplored Reliable Samples to Enhance Test-Time Adaptation
• Revisiting Data Challenges of Computational Pathology: A Pack-based Multiple Instance Learning Training Framework
• Plant identification based on noisy web data: the amazing performance of deep learning (LifeCLEF 2017)
• Concept Learners for Few-Shot Learning
• Learning Data-adaptive Nonparametric Kernels
• Learning Student Networks via Feature Embedding
• ACNet: Strengthening the Kernel Skeletons for Powerful CNN via Asymmetric Convolution Blocks
• FerretNet: Efficient Synthetic Image Detection via Local Pixel Dependencies
• Learning to see across Domains and Modalities
• A State-of-the-art Survey of Artificial Neural Networks for Whole-slide Image Analysis:from Popular Convolutional Neural Networks to Potential Visual Transformers
• Transformation-based Adversarial Video Prediction on Large-Scale Data
• On the distance between two neural networks and the stability of learning
• Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data
• Meteosat Third Generation imagery improves CNN-based SSI retrieval
• Blind Inpainting of Large-scale Masks of Thin Structures with Adversarial and Reinforcement Learning
• SB-MTL: Score-based Meta Transfer-Learning for Cross-Domain Few-Shot Learning
• More Data, Worse Decisions? Preference Reversals in Neural Networks under Gram Incompatibility
• Edge Prediction for Roof Wireframe Reconstruction with Transformers
• SNAC-Pack 2.0: Scaled-Out Surrogate Neural Architecture Codesign
• Recurrence along Depth: Deep Convolutional Neural Networks with Recurrent Layer Aggregation
• What is the Effect of Importance Weighting in Deep Learning?
• Data-Driven Sparse Structure Selection for Deep Neural Networks
• Mirror Descent View for Neural Network Quantization
• Semantic Understanding of Scenes Through the ADE20K Dataset
• A CNN Approach to Simultaneously Count Plants and Detect Plantation-Rows from UAV Imagery
• FabToys
• Evidence Networks: simple losses for fast, amortized, neural Bayesian model comparison
• Vegetation structural shift tells environmental changes on the Tibetan Plateau over 40 years
• Composition-Aware Image Aesthetics Assessment
• Thanks for Nothing: Predicting Zero-Valued Activations with Lightweight Convolutional Neural Networks
• Inductive Bias of Gradient Descent based Adversarial Training on Separable Data
• DMC-Net: Generating Discriminative Motion Cues for Fast Compressed Video Action Recognition
• A contrastive rule for meta-learning
• An Efficient and Automated Classification System for Rocks Based on Visually Explainable Deep Learning
• LeafDNet: Transforming Leaf Disease Diagnosis Through Deep Transfer Learning
• Accurate Retinal Vessel Segmentation via Octave Convolution Neural Network
• Efficient Heuristic Generation for Robot Path Planning with Recurrent Generative Model
• Learning Equivariant Representations
• Analysis of Hyper-Parameters for Small Games: Iterations or Epochs in Self-Play?
• Multi-concept adversarial attacks
• Understanding Self-supervised Learning with Dual Deep Networks
• Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation
• Scaling Up Exact Neural Network Compression by ReLU Stability
• Optical Wavelength Guided Self-Supervised Feature Learning For Galaxy Cluster Richness Estimate
• Self-Supervised Learning for Domain Adaptation on Point-Clouds
• Deep-STORM: super-resolution single-molecule microscopy by deep learning
• An Features Extraction and Recognition Method for Underwater Acoustic Target Based on ATCNN
• ThumbNet: One Thumbnail Image Contains All You Need for Recognition
• 3D Scattering Tomography by Deep Learning with Architecture Tailored to Cloud Fields
• Graphs for deep learning representations
• Generalizing Emergent Communication
• LLMulator: Generalizable Cost Modeling for Dataflow Accelerators with Input-Adaptive Control Flow
• Text Steganalysis with Attentional LSTM-CNN
• Focal Frequency Loss for Image Reconstruction and Synthesis
• Probabilistic Runtime Verification, Evaluation and Risk Assessment of Visual Deep Learning Systems
• A Kernel Space-based Multidimensional Sparse Model for Dynamic PET Image Denoising
• MK-UNet: Multi-kernel Lightweight CNN for Medical Image Segmentation
• Machine learning approach to single-shot multiparameter estimation for the non-linear Schrödinger equation
• Robustness Feature Adapter for Efficient Adversarial Training
• End-to-End Spectro-Temporal Graph Attention Networks for Speaker Verification Anti-Spoofing and Speech Deepfake Detection
• Exploring Machine Learning Models for Physical Dose Calculation in Carbon Ion Therapy Using Heterogeneous Imaging Data -- A Proof of Concept Study
• On Mutual Information Neural Estimation for Localization
• Modeling Human Motion with Quaternion-based Neural Networks
• CSDformer: A Conversion Method for Fully Spike-Driven Transformer
• Deep Clustering for Unsupervised Learning of Visual Features
• Attentional Pooling for Action Recognition
• Self-Supervised Discovery of Neural Circuits in Spatially Patterned Neural Responses with Graph Neural Networks
• SOLAR: Switchable Output Layer for Accuracy and Robustness in Once-for-All Training
• Single Path One-Shot Neural Architecture Search with Uniform Sampling
• Learning Safety for Obstacle Avoidance via Control Barrier Functions
• PlaNet - Photo Geolocation with Convolutional Neural Networks
• PAN: Pillars-Attention-Based Network for 3D Object Detection
• Deep Learning Empowered Super-Resolution: A Comprehensive Survey and Future Prospects
• RangeSAM: On the Potential of Visual Foundation Models for Range-View represented LiDAR segmentation
• The Distribution Shift Problem in Transportation Networks using Reinforcement Learning and AI
• Rethinking "Batch" in BatchNorm
• Towards Multi-Scale Style Control for Expressive Speech Synthesis
• Physics-Informed GCN-LSTM Framework for Long-Term Forecasting of 2D and 3D Microstructure Evolution
• Crafting GBD-Net for Object Detection
• Being Bayesian about Categorical Probability
• Training Larger Networks for Deep Reinforcement Learning
• Unsupervised Object-Level Representation Learning from Scene Images
• Task-agnostic Continual Learning with Hybrid Probabilistic Models
• FedKLPR: Personalized Federated Learning for Person Re-Identification with Adaptive Pruning
• Incorporating Visual Cortical Lateral Connection Properties into CNN: Recurrent Activation and Excitatory-Inhibitory Separation
• Progressive Identification of True Labels for Partial-Label Learning
• Exploring the Relationship between Brain Hemisphere States and Frequency Bands through Deep Learning Optimization Techniques
• DSpAST: Disentangled Representations for Spatial Audio Reasoning with Large Language Models
• Noise Supervised Contrastive Learning and Feature-Perturbed for Anomalous Sound Detection
• Self Identity Mapping
• Plug-and-Play PDE Optimization for 3D Gaussian Splatting: Toward High-Quality Rendering and Reconstruction
• On the Out-of-Distribution Backdoor Attack for Federated Learning
• Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks
• Learning towards Minimum Hyperspherical Energy
• Bridging Performance Gaps for ECG Foundation Models: A Post-Training Strategy
• A Learnable Fully Interacted Two-Tower Model for Pre-Ranking System
• Reversible Deep Equilibrium Models
• CLIFF: Continual Learning for Incremental Flake Features in 2D Material Identification
• Temporal Attentive Alignment for Large-Scale Video Domain Adaptation
• BackPACK: Packing more into backprop
• A Loss Function for Generative Neural Networks Based on Watson's Perceptual Model
• TSIT: A Simple and Versatile Framework for Image-to-Image Translation
• On the Bias-Variance Tradeoff: Textbooks Need an Update
• Denoising IMU Gyroscopes with Deep Learning for Open-Loop Attitude Estimation
• SubSpectral Normalization for Neural Audio Data Processing
• Attention Convolutional Binary Neural Tree for Fine-Grained Visual Categorization
• Learning Deep Image Priors for Blind Image Denoising
• 3D Quasi-Recurrent Neural Network for Hyperspectral Image Denoising
• On Empirical Comparisons of Optimizers for Deep Learning
• Batch-Shaping for Learning Conditional Channel Gated Networks
• BI-GCN: Boundary-Aware Input-Dependent Graph Convolution Network for Biomedical Image Segmentation
• Learning Deep Representations of Fine-grained Visual Descriptions
• Geolocation-Aware Robust Spoken Language Identification
• Bootstrap your own latent: A new approach to self-supervised Learning
• MaX-DeepLab: End-to-End Panoptic Segmentation with Mask Transformers
• DeepMET: Improving missing transverse momentum estimation with a deep neural network
• Optimizer Fusion: Efficient Training with Better Locality and Parallelism
• Data augmentation and image understanding
• Artificial neural networks for neuroscientists: A primer
• Is Attention Better Than Matrix Decomposition?
• Jet tagging in the Lund plane with graph networks
• Normalization Techniques in Training DNNs: Methodology, Analysis and Application
• Convolutional Neural Networks for Accurate Measurement of Train Speed
• Impact of a Sharpness Based Loss Function for Removing Out-of-Focus Blur
• Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks
• DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds
• Machine Learning-Driven Predictive Resource Management in Complex Science Workflows
• An Attention-Based Deep Learning Approach for Sleep Stage Classification With Single-Channel EEG
• Promoting Shape Bias in CNNs: Frequency-Based and Contrastive Regularization for Corruption Robustness
• Video Super-resolution with Temporal Group Attention
• Neural networks in the search for fast radio bursts with RATAN-600
• Geometrically Constrained and Token-Based Probabilistic Spatial Transformers
• Optimal message passing for molecular prediction is simple, attentive and spatial
• Competitive Inner-Imaging Squeeze and Excitation for Residual Network
• An Efficient Dual-Line Decoder Network with Multi-Scale Convolutional Attention for Multi-organ Segmentation
• Deep Learning for Generic Object Detection: A Survey
• Rethinking Channel Dimensions for Efficient Model Design
• FedBiF: Communication-Efficient Federated Learning via Bits Freezing
• Towards Stabilizing Batch Statistics in Backward Propagation of Batch Normalization
• A Capsule-unified Framework of Deep Neural Networks for Graphical Programming
• LoFT: Parameter-Efficient Fine-Tuning for Long-tailed Semi-Supervised Learning in Open-World Scenarios
• Purge-Gate: Backpropagation-Free Test-Time Adaptation for Point Clouds Classification via Token Purging
• Multigrid Neural Architectures
• Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
• MSDANet: A Multiscale Dual-Channel Spatial Attention Network with Depthwise Separable Convolution for Hyperspectral Image Classification
• TriagerX: Dual Transformers for Bug Triaging Tasks with Content and Interaction Based Rankings
• Network Pruning via Transformable Architecture Search
• Exploring Simple Siamese Representation Learning
• A holistic approach to polyphonic music transcription with neural networks
• Attention-based cross-modal fusion for audio-visual voice activity detection in musical video streams
• Learning Explainable Imaging-Genetics Associations Related to a Neurological Disorder
• Attentional Feature Fusion
• Low-Fidelity End-to-End Video Encoder Pre-training for Temporal Action Localization
• Residual Dense Network for Image Restoration
• PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding
• Variational Depth Search in ResNets
• Fault Tolerant Control of a Quadcopter using Reinforcement Learning
• Root Mean Square Layer Normalization
• Using Optimal Transport Aligned Latent Embeddings for Separated Flow Analysis
• Neural Anisotropy Directions
• Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks
• Breaking the Conventional Forward-Backward Tie in Neural Networks: Activation Functions
• Evaluating the Impact of Adversarial Attacks on Traffic Sign Classification using the LISA Dataset
• Improving Consistency and Correctness of Sequence Inpainting using Semantically Guided Generative Adversarial Network
• Integrating Spatial and Semantic Embeddings for Stereo Sound Event Localization in Videos
• RotoGrad: Gradient Homogenization in Multitask Learning
• On the Reproducibility of "FairCLIP: Harnessing Fairness in Vision-Language Learning''
• Lookup multivariate Kolmogorov-Arnold Networks
• Self-Adaptive Training: beyond Empirical Risk Minimization
• Micro-Expression Recognition via Fine-Grained Dynamic Perception
• Regularization with Latent Space Virtual Adversarial Training
• RepVGG: Making VGG-style ConvNets Great Again
• Unity Style Transfer for Person Re-Identification
• Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks
• Fine-grained Video Categorization with Redundancy Reduction Attention
• Deep learning-based phase prediction of high-entropy alloys: Optimization, generation, and explanation
• Unpaired Image Super-Resolution using Pseudo-Supervision
• 3DPillars: Pillar-based two-stage 3D object detection
• Segmentation and Tracking of Eruptive Solar Phenomena with Convolutional Neural Networks
• Intelligent Home 3D: Automatic 3D-House Design from Linguistic Descriptions Only
• Deep Reinforcement Learning for Ranking Utility Tuning in the Ad Recommender System at Pinterest
• Q-SAM2: Accurate Quantization for Segment Anything Model 2
• COGITAO: A Visual Reasoning Framework To Study Compositionality & Generalization
• Adapt in the Wild: Test-Time Entropy Minimization with Sharpness and Feature Regularization
• Empirical Studies on the Properties of Linear Regions in Deep Neural Networks
• VCMamba: Bridging Convolutions with Multi-Directional Mamba for Efficient Visual Representation
• Approximated Oracle Filter Pruning for Destructive CNN Width Optimization
• Heard More Than Heard: An Audio Steganography Method Based on GAN
• Generalizable Model-agnostic Semantic Segmentation via Target-specific Normalization
• Spatiotemporal Pyramid Network for Video Action Recognition
• Dari Barisan ke Pakatan: berubahnya dinamiks Pilihan Raya UmumKuala Lumpur 1955-2013
• Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain Generalization
• Differentiating through the Fréchet Mean
• Simpler Certified Radius Maximization by Propagating Covariances
• Center-based 3D Object Detection and Tracking
• Insights from Gradient Dynamics: Gradient Autoscaled Normalization
• Initialization Schemes for Kolmogorov-Arnold Networks: An Empirical Study
• Temporal social network modeling of mobile connectivity data with graph neural networks
• Deep Learning for High Speed Optical Coherence Elastography with a Fiber Scanning Endoscope
• Understanding deep learning requires rethinking generalization
• Network Implosion: Effective Model Compression for ResNets via Static Layer Pruning and Retraining
• Sharp Minima Can Generalize For Deep Nets
• StableSleep: Source-Free Test-Time Adaptation for Sleep Staging with Lightweight Safety Rails
• Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks
• The EPIC-KITCHENS Dataset: Collection, Challenges and Baselines
• Making EfficientNet More Efficient: Exploring Batch-Independent Normalization, Group Convolutions and Reduced Resolution Training
• Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
• Deep neural network for pixel-level electromagnetic particle identification in the MicroBooNE liquid argon time projection chamber
• Deep Group-shuffling Random Walk for Person Re-identification
• Facial Expression Editing with Continuous Emotion Labels
• VISP: Volatility Informed Stochastic Projection for Adaptive Regularization
• ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias
• Training GANs with Stronger Augmentations via Contrastive Discriminator
• A Runtime-Based Computational Performance Predictor for Deep Neural Network Training
• Federated Generative Adversarial Learning
• Learning Selective Mutual Attention and Contrast for RGB-D Saliency Detection
• Stochastic Function Norm Regularization of Deep Networks
• Modeling and benchmarking quantum optical neurons for efficient neural computation
• Physics-Guided Neural Networks for Constructing Nucleon-Nucleon Inverse Potentials
• Domain Adaptation via Feature Refinement
• Generalization by design: Shortcuts to Generalization in Deep Learning
• Towards Out-Of-Distribution Generalization: A Survey
• A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS
• Summarize and Search: Learning Consensus-aware Dynamic Convolution for Co-Saliency Detection
• Learning to match transient sound events using attentional similarity for few-shot sound recognition
• From Synthetic to Real: Unsupervised Domain Adaptation for Animal Pose Estimation
• CalibDNN: Multimodal Sensor Calibration for Perception Using Deep Neural Networks
• What Expressivity Theory Misses: Message Passing Complexity for GNNs
• 3D Pose Transfer with Correspondence Learning and Mesh Refinement
• Learning to Prune in Training via Dynamic Channel Propagation
• CO2: Consistent Contrast for Unsupervised Visual Representation Learning
• CNN with large memory layers
• Optimized Weight Initialization on the Stiefel Manifold for Deep ReLU Neural Networks
• An exact multiple-time-step variational formulation for the committor and the transition rate
• Deep Learning for CMB Foreground Removal and Beam Deconvolution: A U-Net GAN Approach
• Activation Subspaces for Out-of-Distribution Detection
• Deep Learning on Attributed Graphs: A Journey from Graphs to Their Embeddings and Back
• Evaluation Function Approximation for Scrabble
• lifeXplore at the Lifelog Search Challenge 2020
• Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs
• Mini Autonomous Car Driving based on 3D Convolutional Neural Networks
• 3D Photo Stylization: Learning to Generate Stylized Novel Views from a Single Image
• Rethinking Layer-wise Model Merging through Chain of Merges
• Dual Student: Breaking the Limits of the Teacher in Semi-supervised Learning
• Local Virtual Nodes for Alleviating Over-Squashing in Graph Neural Networks
• Self-organized learning emerges from coherent coupling of critical neurons
• The Pitfall of More Powerful Autoencoders in Lidar-Based Navigation
• SimShear: Sim-to-Real Shear-based Tactile Servoing
• A Chain Graph Interpretation of Real-World Neural Networks
• Improved Adversarial Robustness by Reducing Open Space Risk via Tent Activations
• Learning Local Feature Descriptor with Motion Attribute for Vision-based Localization
• Exploring Randomly Wired Neural Networks for Image Recognition
• Neuromorphic Deep Learning Machines
• Conditionally adaptive augmented Lagrangian method for physics-informed learning of forward and inverse problems
• SPACE: Unsupervised Object-Oriented Scene Representation via Spatial Attention and Decomposition
• Filter then Attend: Improving attention-based Time Series Forecasting with Spectral Filtering
• Weisfeiler and Lehman Go Cellular: CW Networks
• The Impact of Reinitialization on Generalization in Convolutional Neural Networks
• CoPE: Conditional image generation using Polynomial Expansions
• How Does Batch Normalization Help Optimization?
• Video Representation Learning with Visual Tempo Consistency
• Whitening for Self-Supervised Representation Learning
• Hierarchical Contrastive Motion Learning for Video Action Recognition
• Backprop with Approximate Activations for Memory-efficient Network Training
• JEDI-linear: Fast and Efficient Graph Neural Networks for Jet Tagging on FPGAs
• Multiscale Deep Equilibrium Models
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• GRADSTOP: Early Stopping of Gradient Descent via Posterior Sampling
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• Glo-VLMs: Leveraging Vision-Language Models for Fine-Grained Diseased Glomerulus Classification
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• Embedding Transfer with Label Relaxation for Improved Metric Learning
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• HeteroMRI: Robust white matter abnormality classification across multi-scanner MRI data
• Self-supervised learning for multiplexing super-resolution confocal microscopy
• Direct Prediction of Steady-State Flow Fields in Meshed Domain with Graph Networks
• Range-Angle Likelihood Maps for Indoor Positioning Using Deep Neural Networks
• RED-NET: A Recursive Encoder-Decoder Network for Edge Detection
• Deploying Models to Non-participating Clients in Federated Learning without Fine-tuning: A Hypernetwork-based Approach
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• Adversarial Mixing Policy for Relaxing Locally Linear Constraints in Mixup
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• Recognizing Handwritten Mathematical Expressions as LaTex Sequences Using a Multiscale Robust Neural Network
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• Dissecting Hessian: Understanding Common Structure of Hessian in Neural Networks
• Dual-view Molecule Pre-training
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• Deep Template Matching for Pedestrian Attribute Recognition with the Auxiliary Supervision of Attribute-wise Keypoints
• Noise Matters: Optimizing Matching Noise for Diffusion Classifiers
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• Deeply Equal-Weighted Subset Portfolios
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• Distribution Matching in Variational Inference
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• The Vanishing Gradient Problem for Stiff Neural Differential Equations
• FASTER Recurrent Networks for Efficient Video Classification
• Perspective from a Broader Context: Can Room Style Knowledge Help Visual Floorplan Localization?
• Boosting Sensitivity to HH→ bb γγ with Graph Neural Networks and XGBoost
• PrivPy: Enabling Scalable and General Privacy-Preserving Machine Learning
• A Note on Knowledge Distillation Loss Function for Object Classification
• A Conditional GAN for Tabular Data Generation with Probabilistic Sampling of Latent Subspaces
• Image-Based Jet Analysis
• Nonlocal Neural Networks, Nonlocal Diffusion and Nonlocal Modeling
• Space-Time-Separable Graph Convolutional Network for Pose Forecasting
• Classification with Rejection Based on Cost-sensitive Classification
• Benchmarking Massively Parallelized Multi-Task Reinforcement Learning for Robotics Tasks
• BS-NAS: Broadening-and-Shrinking One-Shot NAS with Searchable Numbers of Channels
• Do We Need Zero Training Loss After Achieving Zero Training Error?
• Orthonormal Product Quantization Network for Scalable Face Image Retrieval
• Multilingual Political Views of Large Language Models: Identification and Steering
• Pulling Back the Curtain on Deep Networks
• Real-time People Tracking and Identification from Sparse mm-Wave Radar Point-clouds
• Deep Likelihood Network for Image Restoration with Multiple Degradation Levels
• Efficient Neural Architecture Transformation Searchin Channel-Level for Object Detection
• Boost Self-Supervised Dataset Distillation via Parameterization, Predefined Augmentation, and Approximation
• From Sublinear to Linear: Fast Convergence in Deep Networks via Locally Polyak-Lojasiewicz Regions
• Exploring Probabilistic Modeling Beyond Domain Generalization for Semantic Segmentation
• Neural Bootstrapper
• Relational Data Synthesis using Generative Adversarial Networks: A Design Space Exploration
• Mask-Free Audio-driven Talking Face Generation for Enhanced Visual Quality and Identity Preservation
• Sound2Sight: Generating Visual Dynamics from Sound and Context
• False Negative Distillation and Contrastive Learning for Personalized Outfit Recommendation
• Combolutional Neural Networks
• Improving Protein Gamma-Turn Prediction Using Inception Capsule Networks
• Learning to See Inside Opaque Liquid Containers using Speckle Vibrometry
• Graph Generative Adversarial Networks for Sparse Data Generation in High Energy Physics
• Learning to Paint With Model-based Deep Reinforcement Learning
• Unsupervised Visual Representation Learning by Online Constrained K-Means
• A Multimodal Architecture for Endpoint Position Prediction in Team-based Multiplayer Games
• Progressive Pose Attention Transfer for Person Image Generation
• Your Attention Matters: to Improve Model Robustness to Noise and Spurious Correlations
• STARN-GAT: A Multi-Modal Spatio-Temporal Graph Attention Network for Accident Severity Prediction
• Surrogate-assisted Particle Swarm Optimisation for Evolving Variable-length Transferable Blocks for Image Classification
• An empirical comparison of deep-neural-network architectures for next activity prediction using context-enriched process event logs
• Designing Counterfactual Generators using Deep Model Inversion
• Robust Deep Graph Based Learning for Binary Classification
• Gradient Harmonized Single-stage Detector
• Facial Emotion Recognition: State of the Art Performance on FER2013
• A mini-batch training strategy for deep subspace clustering networks
• An Efficient Agreement Mechanism in CapsNets By Pairwise Product
• Do We Need Sound for Sound Source Localization?
• A Systematic Literature Review on the Use of Deep Learning in Software Engineering Research
• Probabilistic bounds on neuron death in deep rectifier networks
• Semi-Supervised Learning with Ladder Networks
• RADDet: Range-Azimuth-Doppler based Radar Object Detection for Dynamic Road Users
• Hyper-Parameter Sweep on AlphaZero General
• Enhancing Fatigue Detection through Heterogeneous Multi-Source Data Integration and Cross-Domain Modality Imputation
• Attention-based Ensemble for Deep Metric Learning
• BRIEF: Backward Reduction of CNNs with Information Flow Analysis
• Noise Robust Generative Adversarial Networks
• On Modelling Label Uncertainty in Deep Neural Networks: Automatic Estimation of Intra-observer Variability in 2D Echocardiography Quality Assessment
• Attention Guided Low-light Image Enhancement with a Large Scale Low-light Simulation Dataset
• Adaptive Loss Scaling for Mixed Precision Training
• The Six Fronts of the Generative Adversarial Networks
• Interpretable Convolutional Filters with SincNet
• Densely connected normalizing flows
• Perspective from a Higher Dimension: Can 3D Geometric Priors Help Visual Floorplan Localization?
• A Deep Learning based Framework to Detect and Recognize Humans using Contactless Palmprints in the Wild
• Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting
• Reduced-order modeling of large-scale turbulence using Koopman β-variational autoencoders
• Band Attention Convolutional Networks For Hyperspectral Image Classification
• NodeDrop: A Condition for Reducing Network Size without Effect on Output
• Collaborative Spatio-temporal Feature Learning for Video Action Recognition
• ProGraML: Graph-based Deep Learning for Program Optimization and Analysis
• Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs
• Concept Probing: Where to Find Human-Defined Concepts (Extended Version)
• Convolutional Neural Network for emotion recognition to assist psychiatrists and psychologists during the COVID-19 pandemic: experts opinion
• Exploring the Vision Processing Unit as Co-processor for Inference
• Joint Spatial and Layer Attention for Convolutional Networks
• Cluster Contrast for Unsupervised Person Re-Identification
• A* Tree Search for Portfolio Management
• Continual Learning in Deep Networks: an Analysis of the Last Layer
• Automatic Segmentation, Localization, and Identification of Vertebrae in 3D CT Images Using Cascaded Convolutional Neural Networks
• Self-Distilled Self-Supervised Representation Learning
• Semantic Correlation Promoted Shape-Variant Context for Segmentation
• Orthogonal Convolutional Neural Networks
• Q-Net: A Quantitative Susceptibility Mapping-based Deep Neural Network for Differential Diagnosis of Brain Iron Deposition in Hemochromatosis
• EEG-ConvTransformer for Single-Trial EEG based Visual Stimuli Classification
• SetGAN: Improving the stability and diversity of generative models through a permutation invariant architecture
• Pre-Training Graph Neural Networks for Generic Structural Feature Extraction
• Scaling Spike-Driven Transformer With Efficient Spike Firing Approximation Training
• End-to-End Learning of Geometric Deformations of Feature Maps for Virtual Try-On
• All-In-One: Artificial Association Neural Networks
• Simple2Complex: Global Optimization by Gradient Descent
• #StayHome or #Marathon? Social Media Enhanced Pandemic Surveillance on Spatial-temporal Dynamic Graphs
• From augmented microscopy to the topological transformer: a new approach in cell image analysis for Alzheimer's research
• Redesigning Fully Convolutional DenseUNets for Large Histopathology Images
• Towards Deep and Efficient: A Deep Siamese Self-Attention Fully Efficient Convolutional Network for Change Detection in VHR Images
• Unsupervised Domain Adaptation for Retinal Vessel Segmentation with Adversarial Learning and Transfer Normalization
• Reconstructing a dynamical system and forecasting time series by self-consistent deep learning
• Emulating ultrafast dissipative quantum dynamics with deep neural networks
• Information-Theoretic Local Minima Characterization and Regularization
• Unpaired Single-Image Depth Synthesis with cycle-consistent Wasserstein GANs
• Training-Time-Friendly Network for Real-Time Object Detection
• Improved Transformer for High-Resolution GANs
• ACNe: Attentive Context Normalization for Robust Permutation-Equivariant Learning
• Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units
• Revisiting Training Strategies and Generalization Performance in Deep Metric Learning
• Guided Collaborative Training for Pixel-wise Semi-Supervised Learning
• Proxy-Normalizing Activations to Match Batch Normalization while Removing Batch Dependence
• Multi-Adapter RGBT Tracking
• PFDet: 2nd Place Solution to Open Images Challenge 2018 Object Detection Track
• Beyond Fixed Grid: Learning Geometric Image Representation with a Deformable Grid
• ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning
• NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results
• CelebHair: A New Large-Scale Dataset for Hairstyle Recommendation based on CelebA
• SCNet: A Neural Network for Automated Side-Channel Attack
• Multi-channel Deep 3D Face Recognition
• Circle Loss: A Unified Perspective of Pair Similarity Optimization
• Multi-Channel Graph Convolutional Networks
• DARNet: Deep Active Ray Network for Building Segmentation
• MBNet: MOS Prediction for Synthesized Speech with Mean-Bias Network
• Residual Continual Learning
• Rotate-and-Render: Unsupervised Photorealistic Face Rotation from Single-View Images
• Uniform Sampling over Episode Difficulty
• Memory-efficient Embedding for Recommendations
• Enigma: An Efficient Model for Deciphering Regulatory Genomics
• Trimap-guided Feature Mining and Fusion Network for Natural Image Matting
• Conflicting Bundles: Adapting Architectures Towards the Improved Training of Deep Neural Networks
• Mapping Motor Cortex Stimulation to Muscle Responses: A Deep Neural Network Modeling Approach
• Optimizing the Whole-life Cost in End-to-end CNN Acceleration
• Curriculum learning for multilevel budgeted combinatorial problems
• Reducing Inference Latency with Concurrent Architectures for Image Recognition
• An End-to-End Text-independent Speaker Verification Framework with a Keyword Adversarial Network
• One Step Closer: Creating the Future to Boost Monocular Semantic Scene Completion
• Deep Residual Learning in Spiking Neural Networks
• Hyperbolic Deep Learning for Foundation Models: A Survey
• Structural Connectome Harmonization Using Deep Learning: The Strength of Graph Neural Networks
• DNT: a Deeply Normalized Transformer that can be trained by Momentum SGD
• Manifold-preserved GANs
• X-volution: On the unification of convolution and self-attention
• On Large Batch Training and Sharp Minima: A Fokker-Planck Perspective
• Attribution Mask: Filtering Out Irrelevant Features By Recursively Focusing Attention on Inputs of DNNs
• Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond
• Disentangled Representations for Domain-generalized Cardiac Segmentation
• Out-of-distribution data supervision towards biomedical semantic segmentation
• BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder Architecture
• A Seq-to-Seq Transformer Premised Temporal Convolutional Network for Chinese Word Segmentation
• A New Look at Ghost Normalization
• Semi-Supervised Learning by Label Gradient Alignment
• High Speed and High Dynamic Range Video with an Event Camera
• Online Training and Pruning of Deep Reinforcement Learning Networks
• SimPose: Effectively Learning DensePose and Surface Normals of People from Simulated Data
• Improving KAN with CDF normalization to quantiles
• Long Short-Term Transformer for Online Action Detection
• Cluster Contrast for Unsupervised Visual Representation Learning
• New Benchmarks for Learning on Non-Homophilous Graphs
• Prototypical Progressive Alignment and Reweighting for Generalizable Semantic Segmentation
• Revisiting Diffusion Models: From Generative Pre-training to One-Step Generation
• Speed/accuracy trade-offs for modern convolutional object detectors
• Vector representations of text data in deep learning
• Interpretable Prediction of Lymph Node Metastasis in Rectal Cancer MRI Using Variational Autoencoders
• Exploring the robustness of TractOracle methods in RL-based tractography
• Weakly Supervised Person Re-ID: Differentiable Graphical Learning and A New Benchmark
• Stochastic Adversarial Koopman Model for Dynamical Systems
• Episodic Training for Domain Generalization
• Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages
• Learning to Sample the Most Useful Training Patches from Images
• Macular OCT Classification Using a Multi-Scale Convolutional Neural Network Ensemble
• FA-GANs: Facial Attractiveness Enhancement with Generative Adversarial Networks on Frontal Faces
• SPIN: A High Speed, High Resolution Vision Dataset for Tracking and Action Recognition in Ping Pong
• MonoRUn: Monocular 3D Object Detection by Reconstruction and Uncertainty Propagation
• BYOL works even without batch statistics
• Deep Neural Networks for Active Wave Breaking Classification
• Improving Deep Neural Network with Multiple Parametric Exponential Linear Units
• Exploiting Contextual Information with Deep Neural Networks
• Cross-Layer Distillation with Semantic Calibration
• Machine learning moment closure models for the radiative transfer equation III: enforcing hyperbolicity and physical characteristic speeds
• A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient Backpropagation
• Token Perturbation Guidance for Diffusion Models
• Gradient Origin Networks
• ContraGAN: Contrastive Learning for Conditional Image Generation
• Boosting Scene Character Recognition by Learning Canonical Forms of Glyphs
• Modeling Tabular data using Conditional GAN
• Deep Low-Shot Learning for Biological Image Classification and Visualization from Limited Training Samples
• EnlightenGAN: Deep Light Enhancement Without Paired Supervision
• RepMLP: Re-parameterizing Convolutions into Fully-connected Layers for Image Recognition
• StarEnhancer: Learning Real-Time and Style-Aware Image Enhancement
• Effective and Efficient Dropout for Deep Convolutional Neural Networks
• Cross-X Learning for Fine-Grained Visual Categorization
• Cascade R-CNN: High Quality Object Detection and Instance Segmentation
• Towards Fair Deep Anomaly Detection
• Improving Graph Neural Networks with Simple Architecture Design
• EPNet: Enhancing Point Features with Image Semantics for 3D Object Detection
• Video Temporal Relationship Mining for Data-Efficient Person Re-identification
• Recurrent Neural Networks for Time Series Forecasting: Current Status and Future Directions
• Predicting brain-age from raw T 1 -weighted Magnetic Resonance Imaging data using 3D Convolutional Neural Networks
• Real-Time Anchor-Free Single-Stage 3D Detection with IoU-Awareness
• Mutual exclusivity as a challenge for deep neural networks
• Generating Electronic Health Records with Multiple Data Types and Constraints
• An Adaptive Method Stabilizing Activations for Enhanced Generalization
• Almost Sure Asymptotic Freeness of Neural Network Jacobian with Orthogonal Weights
• Towards a Better Understanding and Regularization of GAN Training Dynamics
• Versatile Inverse Reinforcement Learning via Cumulative Rewards
• Multi-stream 3D FCN with Multi-scale Deep Supervision for Multi-modality Isointense Infant Brain MR Image Segmentation
• Deep Learning Based Early Diagnostics of Parkinsons Disease
• Accumulated Polar Feature-based Deep Learning for Efficient and Lightweight Automatic Modulation Classification with Channel Compensation Mechanism
• Hierarchical VAEs Know What They Don't Know
• Run, Don't Walk: Chasing Higher FLOPS for Faster Neural Networks
• Parrot: Data-Driven Behavioral Priors for Reinforcement Learning
• Back to Simplicity: How to Train Accurate BNNs from Scratch?
• Faster Neural Network Training with Data Echoing
• Panoptic Feature Pyramid Networks
• Improved Deep Classwise Hashing With Centers Similarity Learning for Image Retrieval
• Unsupervised Learning of Full-Waveform Inversion: Connecting CNN and Partial Differential Equation in a Loop
• Adversarial Dropout for Recurrent Neural Networks
• Progressive Differentiable Architecture Search: Bridging the Depth Gap between Search and Evaluation
• A White Paper on Neural Network Quantization
• Locally Enhanced Self-Attention: Combining Self-Attention and Convolution as Local and Context Terms
• Multimodal Reward Shaping for Efficient Exploration in Reinforcement Learning
• Artificial Intelligence for Pediatric Ophthalmology
• Regularizing Neural Networks via Stochastic Branch Layers
• Find the Conversation Killers: a Predictive Study of Thread-ending Posts
• Predictive Process Model Monitoring using Recurrent Neural Networks
• Unsupervised Anomaly Detection for X-Ray Images
• A Comprehensive Comparison of Multi-Dimensional Image Denoising Methods
• Nested Named Entity Recognition with Partially-Observed TreeCRFs
• Taco-VC: A Single Speaker Tacotron based Voice Conversion with Limited Data
• Transfer Learning-Based Received Power Prediction with Ray-tracing Simulation and Small Amount of Measurement Data
• Recurrent networks improve neural response prediction and provide insights into underlying cortical circuits
• Measuring Robustness to Natural Distribution Shifts in Image Classification
• Network Space Search for Pareto-Efficient Spaces
• Learning to Generate with Memory
• RMAU-NET: A Residual-Multihead-Attention U-Net Architecture for Landslide Segmentation and Detection from Remote Sensing Images
• A Simple Baseline for Semi-supervised Semantic Segmentation with Strong Data Augmentation
• Deep Claim: Payer Response Prediction from Claims Data with Deep Learning
• Locality Guided Neural Networks for Explainable Artificial Intelligence
• DARTS-ASR: Differentiable Architecture Search for Multilingual Speech Recognition and Adaptation
• Gradient flow in the kernel learning problem
• Superposed parameterised quantum circuits
• Self-supervised pre-training with acoustic configurations for replay spoofing detection
• Bringing Cartoons to Life: Towards Improved Cartoon Face Detection and Recognition Systems
• SurfR: Surface Reconstruction with Multi-scale Attention
• Polaritonic Machine Learning for Graph-based Data Analysis
• Pose-Guided Feature Learning with Knowledge Distillation for Occluded Person Re-Identification
• Sequence-Model-Guided Measurement Selection for Quantum State Learning
• Continual Learning with Extended Kronecker-factored Approximate Curvature
• Leveraging Distribution Matching to Make Approximate Machine Unlearning Faster
• A few filters are enough: Convolutional Neural Network for P300 Detection
• Learning Discrete Representations via Information Maximizing Self-Augmented Training
• MixNorm: Test-Time Adaptation Through Online Normalization Estimation
• Spot the Difference: Detection of Topological Changes via Geometric Alignment
• Hierarchical Graph Networks for 3D Human Pose Estimation
• Sharper Convergence Rates for Nonconvex Optimisation via Reduction Mappings
• Confounder-Free Continual Learning via Recursive Feature Normalization
• A Hybrid Multi-Well Hopfield-CNN with Feature Extraction and K-Means for MNIST Classification
• A Recursive Network with Dynamic Attention for Monaural Speech Enhancement
• Topological Planning with Transformers for Vision-and-Language Navigation
• DIsoN: Decentralized Isolation Networks for Out-of-Distribution Detection in Medical Imaging
• Weight-Sharing Neural Architecture Search: A Battle to Shrink the Optimization Gap
• Perceptual Score: What Data Modalities Does Your Model Perceive?
• Admissibility of Stein Shrinkage for Batch Normalization in the Presence of Adversarial Attacks
• Deep Homography Estimation for Dynamic Scenes
• D2Dewarp: Dual Dimensions Geometric Representation Learning Based Document Image Dewarping
• SemRaFiner: Panoptic Segmentation in Sparse and Noisy Radar Point Clouds
• Blind Backdoors in Deep Learning Models
• Confidence-Aware Learning for Camouflaged Object Detection
• GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations
• Mask6D: Masked Pose Priors For 6D Object Pose Estimation
• Predicting inflation with recurrent neural networks
• Energy-Efficient Supervised Learning with a Binary Stochastic Forward-Forward Algorithm
• Designing Adaptive Algorithms Based on Reinforcement Learning for Dynamic Optimization of Sliding Window Size in Multi-Dimensional Data Streams
• MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning
• SILVA Networks as Structured Implicit Layers and Vector Attractors via Dynamic Interaction Fields
• Online Learning to Rank with List-level Feedback for Image Filtering
• Popcorn: Paillier Meets Compression For Efficient Oblivious Neural Network Inference
• Comparative Analysis of CNN and Transformer Architectures with Heart Cycle Normalization for Automated Phonocardiogram Classification
• Asymmetric Valleys: Beyond Sharp and Flat Local Minima
• Unsupervised Deep Learning by Injecting Low-Rank and Sparse Priors
• Batch Normalization with Enhanced Linear Transformation
• How Does BN Increase Collapsed Neural Network Filters?
• An Efficient Method of Training Small Models for Regression Problems with Knowledge Distillation
• φ-Adapt: A Physics-Informed Adaptation Learning Approach to 2D Quantum Material Discovery
• Semi-weakly Supervised Contrastive Representation Learning for Retinal Fundus Images
• Boundary-preserving Mask R-CNN
• Weakly Supervised Deep Recurrent Neural Networks for Basic Dance Step Generation
• A Two-Step Framework for Arbitrage-Free Prediction of the Implied Volatility Surface
• Spatial and Semantic Embedding Integration for Stereo Sound Event Localization and Detection in Regular Videos
• ePointDA: An End-to-End Simulation-to-Real Domain Adaptation Framework for LiDAR Point Cloud Segmentation
• Spooky Action at a Distance: Normalization Layers Enable Side-Channel Spatial Communication
• Recovering Plasticity of Neural Networks via Soft Weight Rescaling
• Enhancing Underwater Images Using Deep Learning with Subjective Image Quality Integration
• Adversarial Examples Improve Image Recognition
• Graph Stacked Hourglass Networks for 3D Human Pose Estimation
• NePTuNe: Neural Powered Tucker Network for Knowledge Graph Completion
• RAFT-Stereo: Multilevel Recurrent Field Transforms for Stereo Matching
• Optimizing Neural Network for Computer Vision task in Edge Device
• Delving into VoxCeleb: environment invariant speaker recognition
• Ex uno plures: Splitting One Model into an Ensemble of Subnetworks
• Structured Convolution Matrices for Energy-efficient Deep learning
• Langevin Cooling for Domain Translation
• Disentangling Transfer and Interference in Multi-Domain Learning
• Growing Efficient Deep Networks by Structured Continuous Sparsification
• Centralized Information Interaction for Salient Object Detection
• Early Convolutions Help Transformers See Better
• Learning Deep Gradient Descent Optimization for Image Deconvolution
• Deep Reinforcement Learning Models Predict Visual Responses in the Brain: A Preliminary Result
• On the Minimal Supervision for Training Any Binary Classifier from Only Unlabeled Data
• Deep End-to-End Alignment and Refinement for Time-of-Flight RGB-D Module
• Dynamical Isometry: The Missing Ingredient for Neural Network Pruning
• Source Free Domain Adaptation with Image Translation
• Performance Analysis of a Foreground Segmentation Neural Network Model
• Direct Quantization for Training Highly Accurate Low Bit-width Deep Neural Networks
• Shakeout: A New Approach to Regularized Deep Neural Network Training
• Hybrid Quantum Generative Adversarial Networks To Inverse Design Metasurfaces For Incident Angle-Independent Unidirectional Transmission
• Radar Tracker: Moving Instance Tracking in Sparse and Noisy Radar Point Clouds
• Partial Order Pruning: for Best Speed/Accuracy Trade-off in Neural Architecture Search
• Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning
• Variational Autoencoders for Deforming 3D Mesh Models
• TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up
• Do ImageNet Classifiers Generalize to ImageNet?
• i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning
• Meta-learning of Pooling Layers for Character Recognition
• FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary
• Machine Learning for CSI Recreation Based on Prior Knowledge
• Transformers Don't Need LayerNorm at Inference Time: Scaling LayerNorm Removal to GPT-2 XL and the Implications for Mechanistic Interpretability
• FNA++: Fast Network Adaptation via Parameter Remapping and Architecture Search
• Regularly Updated Deterministic Policy Gradient Algorithm
• Variational Kolmogorov-Arnold Network
• Universal Adversarial Audio Perturbations
• ArtFlow: Unbiased Image Style Transfer via Reversible Neural Flows
• Deep learning-based stacked models for cyber-attack detection in industrial internet of things
• ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data
• Dynamic Refinement Network for Oriented and Densely Packed Object Detection
• High-Layer Attention Pruning with Rescaling
• Automated Classification of Seizures against Nonseizures: A Deep Learning Approach
• Decoupled Low-light Image Enhancement
• Spectral Metric for Dataset Complexity Assessment
• Hardware-software co-exploration with racetrack memory based in-memory computing for CNN inference in embedded systems
• What Do Neural Networks Learn When Trained With Random Labels?
• Compressive Visual Representations
• Bit Error Robustness for Energy-Efficient DNN Accelerators
• An Empirical Study of the Effects of Sample-Mixing Methods for Efficient Training of Generative Adversarial Networks
• Training Neural Networks Using Features Replay
• BlockSwap: Fisher-guided Block Substitution for Network Compression on a Budget
• Neural Enhancement in Content Delivery Systems: The State-of-the-Art and Future Directions
• De-Simplifying Pseudo Labels to Enhancing Domain Adaptive Object Detection
• m-RevNet: Deep Reversible Neural Networks with Momentum
• Combining Diverse Feature Priors
• Automatic brain tissue segmentation in fetal MRI using convolutional neural networks
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• An Investigation into the Stochasticity of Batch Whitening
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• KISS: Keeping It Simple for Scene Text Recognition
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• Towards the Training of Deeper Predictive Coding Neural Networks
• LiStereo: Generate Dense Depth Maps from LIDAR and Stereo Imagery
• SHIELD: Secure Hypernetworks for Incremental Expansion Learning Defense
• FedWSQ: Efficient Federated Learning with Weight Standardization and Distribution-Aware Non-Uniform Quantization
• AI-Assisted Rapid Crystal Structure Generation Towards a Target Local Environment
• FrontFinder AI: Efficient Identification of Frontal Boundaries over the Continental United States and NOAA’s Unified Surface Analysis Domain Using the UNET3+ Model Architecture
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• Uncover Treasures in DCT: Advancing JPEG Quality Enhancement by Exploiting Latent Correlations
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• Exploring Graph-Transformer Out-of-Distribution Generalization Abilities
• A Large RGB-D Dataset for Semi-supervised Monocular Depth Estimation
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• Hear No Evil: Detecting Gradient Leakage by Malicious Servers in Federated Learning
• Optimizing Data Usage via Differentiable Rewards
• Distillation Guided Residual Learning for Binary Convolutional Neural Networks
• Precise Bayesian Neural Networks
• Graph theory inspired anomaly detection at the LHC
• Temporal Regularization Training: Unleashing the Potential of Spiking Neural Networks
• Convolution with even-sized kernels and symmetric padding
• Learning from Positive and Unlabeled Data with Arbitrary Positive Shift
• Progressive Modality Cooperation for Multi-Modality Domain Adaptation
• Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction
• Disentangled High Quality Salient Object Detection
• Self-Paced Collaborative and Adversarial Network for Unsupervised Domain Adaptation
• Dirty Pixels: Towards End-to-End Image Processing and Perception
• A Low-Compexity Deep Learning Framework For Acoustic Scene Classification
• Generalizing vision-language models to novel domains: A comprehensive survey
• Expressive TTS Training with Frame and Style Reconstruction Loss
• Uncertainty-Aware Lookahead Factor Models for Quantitative Investing
• DeInfoReg: A Decoupled Learning Framework for Better Training Throughput
• Pix2Geomodel: A Next-Generation Reservoir Geomodeling with Property-to-Property Translation
• SynDaCaTE: A Synthetic Dataset For Evaluating Part-Whole Hierarchical Inference
• Terminal Brain Damage: Exposing the Graceless Degradation in Deep Neural Networks Under Hardware Fault Attacks
• Neural Sign Language Translation based on Human Keypoint Estimation
• PDFNet: Pointwise Dense Flow Network for Urban-Scene Segmentation
• Navigating the Deep: Signature Extraction on Deep Neural Networks
• Incentivizing High-quality Participation From Federated Learning Agents
• Decoupling Global and Local Representations via Invertible Generative Flows
• Mitigating Memorization in Sample Selection for Learning with Noisy Labels
• Unsupervised Text Summarization via Mixed Model Back-Translation
• From Pixels to CSI: Distilling Latent Dynamics For Efficient Wireless Resource Management
• A Critique of Self-Expressive Deep Subspace Clustering
• Deep Learning in Ultrasound Elastography Imaging
• TreeNet: A lightweight One-Shot Aggregation Convolutional Network
• Time-Distributed Feature Learning in Network Traffic Classification for Internet of Things
• EFormer: An Effective Edge-based Transformer for Vehicle Routing Problems
• Pretraining Representations for Data-Efficient Reinforcement Learning
• Conditioning Convolutional Segmentation Architectures with Non-Imaging Data
• Stable Gradients for Stable Learning at Scale in Deep Reinforcement Learning
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• Selection Bias Explorations and Debias Methods for Natural Language Sentence Matching Datasets
• When Model Knowledge meets Diffusion Model: Diffusion-assisted Data-free Image Synthesis with Alignment of Domain and Class
• Sequential Policy Gradient for Adaptive Hyperparameter Optimization
• Demonstrating Superresolution in Radar Range Estimation Using a Denoising Autoencoder
• Learning Deep-Latent Hierarchies by Stacking Wasserstein Autoencoders
• Learning Dynamics from Kinematics: Estimating 2D Foot Pressure Maps from Video Frames
• Multi-task Learning For Detecting and Segmenting Manipulated Facial Images and Videos
• The Perception of Phase Intercept Distortion and its Application in Data Augmentation
• ResNets Are Deeper Than You Think
• Proxy Anchor Loss for Deep Metric Learning
• Breaking the Multi-Enhancement Bottleneck: Domain-Consistent Quality Enhancement for Compressed Images
• Efficient Semantic Image Synthesis via Class-Adaptive Normalization
• Cross-Domain First Person Audio-Visual Action Recognition through Relative Norm Alignment
• Leveraging Vision-Language Pre-training for Human Activity Recognition in Still Images
• Convolutional Neural Networks with Dynamic Regularization
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• Guidance Module Network for Video Captioning
• Quizbowl: The Case for Incremental Question Answering
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• Unlearning-Enhanced Website Fingerprinting Attack: Against Backdoor Poisoning in Anonymous Networks
• Neural Machine Translation: A Review and Survey
• Learning Improvement Heuristics for Solving Routing Problems
• End-to-end Learning Improves Static Object Geo-localization in Monocular Video
• ConTNet: Why not use convolution and transformer at the same time?
• Stereo Vision Based Single-Shot 6D Object Pose Estimation for Bin-Picking by a Robot Manipulator
• Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
• Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks
• Data Normalization Strategies for EEG Deep Learning
• Privacy Leakage of SIFT Features via Deep Generative Model based Image Reconstruction
• Towards Earnings Call and Stock Price Movement
• Towards Robust ResNet: A Small Step but A Giant Leap
• Second-Order Neural ODE Optimizer
• Regularizing Class-wise Predictions via Self-knowledge Distillation
• PURS: Personalized Unexpected Recommender System for Improving User Satisfaction
• Automatic CT Segmentation from Bounding Box Annotations using Convolutional Neural Networks
• Connecting Images through Time and Sources: Introducing Low-data, Heterogeneous Instance Retrieval
• Residual Channel Attention Generative Adversarial Network for Image Super-Resolution and Noise Reduction
• MVFNet: Multi-View Fusion Network for Efficient Video Recognition
• AutoEmb: Automated Embedding Dimensionality Search in Streaming Recommendations
• Reconstructing High-resolution Turbulent Flows Using Physics-Guided Neural Networks
• Mitigating Non-Target Speaker Bias in Guided Speaker Embedding
• Temporal Segment Networks for Action Recognition in Videos
• Compression Aware Certified Training
• Structural Design of Convolutional Neural Networks for Steganalysis
• More Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classification
• End-to-End Adversarial Text-to-Speech
• An Empirical Study on Leveraging Scene Graphs for Visual Question Answering
• Appearance-Preserving 3D Convolution for Video-based Person Re-identification
• Broadcasted Residual Learning for Efficient Keyword Spotting
• Are You Convinced? Choosing the More Convincing Evidence with a Siamese Network
• FAD-Net: Frequency-Domain Attention-Guided Diffusion Network for Coronary Artery Segmentation using Invasive Coronary Angiography
• A Layered Self-Supervised Knowledge Distillation Framework for Efficient Multimodal Learning on the Edge
• Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning
• Learning to Adapt Invariance in Memory for Person Re-identification
• Collaborative Video Object Segmentation by Multi-Scale Foreground-Background Integration
• Class-Incremental Learning for Honey Botanical Origin Classification with Hyperspectral Images: A Study with Continual Backpropagation
• Deep Inertial Pose: A deep learning approach for human pose estimation
• Starting Positions Matter: A Study on Better Weight Initialization for Neural Network Quantization
• Post-Training Quantization for Video Matting
• Solving Traffic4Cast Competition with U-Net and Temporal Domain Adaptation
• Vector Representations of Vessel Trees
• Searching for TrioNet: Combining Convolution with Local and Global Self-Attention
• Feature-Based Instance Neighbor Discovery: Advanced Stable Test-Time Adaptation in Dynamic World
• Data-Driven High-Dimensional Statistical Inference with Generative Models
• Hide & Seek: Transformer Symmetries Obscure Sharpness & Riemannian Geometry Finds It
• NILMFormer: Non-Intrusive Load Monitoring that Accounts for Non-Stationarity
• Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley Transform
• Hyperparameter Optimization for Forecasting Stock Returns
• AdaPruner: Adaptive Channel Pruning and Effective Weights Inheritance
• Dirty Road Can Attack: Security of Deep Learning based Automated Lane Centering under Physical-World Attack
• Geometric Disentanglement by Random Convex Polytopes
• Single Image Deraining with Continuous Rain Density Estimation
• Threshold Modulation for Online Test-Time Adaptation of Spiking Neural Networks
• Intriguing properties of adversarial training at scale
• Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation
• Integer Binary-Range Alignment Neuron for Spiking Neural Networks
• How many degrees of freedom do we need to train deep networks: a loss landscape perspective
• Deep Fusion Network for Image Completion
• Reliably Detecting Model Failures in Deployment Without Labels
• U-NetMN and SegNetMN: Modified U-Net and SegNet models for bimodal SAR image segmentation
• An Unsupervised Framework for Dynamic Health Indicator Construction and Its Application in Rolling Bearing Prognostics
• ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games
• Sigsoftmax: Reanalysis of the Softmax Bottleneck
• Flat2Layout: Flat Representation for Estimating Layout of General Room Types
• Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations
• Normalize Filters! Classical Wisdom for Deep Vision
• Bridging the Performance Gap Between Target-Free and Target-Based Reinforcement Learning
• Regularising Deep Networks with Deep Generative Models
• Have you forgotten? A method to assess if machine learning models have forgotten data
• WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis
• The Perfect Match: 3D Point Cloud Matching with Smoothed Densities
• Key Points Estimation and Point Instance Segmentation Approach for Lane Detection
• 3D Human Pose Estimation with Siamese Equivariant Embedding
• Semi-Supervised Learning for Bone Mineral Density Estimation in Hip X-ray Images
• Adapting Off-the-Shelf Source Segmenter for Target Medical Image Segmentation
• Dense Uncertainty Estimation
• Moonshine: Distilling with Cheap Convolutions
• DER: Dynamically Expandable Representation for Class Incremental Learning
• Learning Discriminative Features Via Weights-biased Softmax Loss
• PokeBNN: A Binary Pursuit of Lightweight Accuracy
• CMT: Convolutional Neural Networks Meet Vision Transformers
• Data augmentation instead of explicit regularization
• Set Flow: A Permutation Invariant Normalizing Flow
• Dropout Q-Functions for Doubly Efficient Reinforcement Learning
• Dynamic Neural Networks: A Survey
• Recent Advances in Deep Learning for Object Detection
• Explicitly Conditioned Melody Generation: A Case Study with Interdependent RNNs
• LPRNet: Lightweight Deep Network by Low-rank Pointwise Residual Convolution
• Graph Warp Module: an Auxiliary Module for Boosting the Power of Graph Neural Networks in Molecular Graph Analysis
• Data-dependent Initializations of Convolutional Neural Networks
• Long-Term Feature Banks for Detailed Video Understanding
• Learning Manipulation States and Actions for Efficient Non-prehensile Rearrangement Planning
• Adversarial Loss for Semantic Segmentation of Aerial Imagery
• Improving Ultrasound Tongue Image Reconstruction from Lip Images Using Self-supervised Learning and Attention Mechanism
• SE-MD: A Single-encoder multiple-decoder deep network for point cloud generation from 2D images
• PoliTO-IIT Submission to the EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition
• Multi-Modal Hybrid Deep Neural Network for Speech Enhancement
• PyChain: A Fully Parallelized PyTorch Implementation of LF-MMI for End-to-End ASR
• Tensor Programs II: Neural Tangent Kernel for Any Architecture
• Medical Image Generation using Generative Adversarial Networks
• Towards Data-Free Domain Generalization
• Learning Visual Voice Activity Detection with an Automatically Annotated Dataset
• Learning Maximally Predictive Prototypes in Multiple Instance Learning
• Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes
• Modulating Image Restoration with Continual Levels via Adaptive Feature Modification Layers
• Variance Reduced Local SGD with Lower Communication Complexity
• Predicting Shot Making in Basketball Learnt from Adversarial Multiagent Trajectories
• Spatial Transformer Networks
• A law of robustness for two-layers neural networks
• Learning Expectation of Label Distribution for Facial Age and Attractiveness Estimation
• Incorporating Luminance, Depth and Color Information by a Fusion-based Network for Semantic Segmentation
• How to Train Your Metamorphic Deep Neural Network
• Learning Generalisable Omni-Scale Representations for Person Re-Identification
• Transformer-Based Source-Free Domain Adaptation
• DeeperLab: Single-Shot Image Parser
• Spherical View Synthesis for Self-Supervised 360 Depth Estimation
• Attending Category Disentangled Global Context for Image Classification
• SEVA: Leveraging Single-Step Ensemble of Vicinal Augmentations for Test-Time Adaptation
• A High-Throughput and Power-Efficient FPGA Implementation of YOLO CNN for Object Detection
• Training-free AI for Earth Observation Change Detection using Physics Aware Neuromorphic Networks
• SemiOccam: A Robust Semi-Supervised Image Recognition Network Using Sparse Labels
• StructureNet: Hierarchical Graph Networks for 3D Shape Generation
• Adversarial Spheres
• Comparative Analysis of Fast and High-Fidelity Neural Vocoders for Low-Latency Streaming Synthesis in Resource-Constrained Environments
• Reconciling Modern Deep Learning with Traditional Optimization Analyses: The Intrinsic Learning Rate
• Improved Residual Networks for Image and Video Recognition
• Deep Controllable Backlight Dimming
• An Improving Framework of regularization for Network Compression
• Modeling Musical Structure with Artificial Neural Networks
• Comprehensive Attribute Encoding and Dynamic LSTM HyperModels for Outcome Oriented Predictive Business Process Monitoring
• Fundamental tenis : resep meraih kemenangan / Tony Mottram
• Blending 3D Geometry and Machine Learning for Multi-View Stereopsis
• Decoupled Appearance and Motion Learning for Efficient Anomaly Detection in Surveillance Video
• Layer-wise Conditioning Analysis in Exploring the Learning Dynamics of DNNs
• MiniSeg: An Extremely Minimum Network for Efficient COVID-19 Segmentation
• RePr: Improved Training of Convolutional Filters
• An Ensemble with Shared Representations Based on Convolutional Networks for Continually Learning Facial Expressions
• Real-time RGBD-based Extended Body Pose Estimation
• Neural Network Pruning with Residual-Connections and Limited-Data
• Fine-grained Optimization of Deep Neural Networks
• Simple, Good, Fast: Self-Supervised World Models Free of Baggage
• A Dynamic Transformer Network for Vehicle Detection
• Skeleton-Based Online Action Prediction Using Scale Selection Network
• Towards Recognizing New Semantic Concepts in New Visual Domains
• Semantic similarity metrics for learned image registration
• Equivariant Subgraph Aggregation Networks
• A Memory-Augmented Neural Network Model of Abstract Rule Learning
• RadarNet: Exploiting Radar for Robust Perception of Dynamic Objects
• Fully-Convolutional Intensive Feature Flow Neural Network for Text Recognition
• Improving the Reproducibility of Deep Learning Software: An Initial Investigation through a Case Study Analysis
• Exchangeability in Neural Network and its Application to Dynamic Pruning
• Why Gradients Rapidly Increase Near the End of Training
• Knowledge Distillation: A Survey
• EWGN: Elastic Weight Generation and Context Switching in Deep Learning
• Online trajectory recovery from offline handwritten Japanese kanji characters
• Quotient Network -- A Network Similar to ResNet but Learning Quotients
• Hidden Representation Clustering with Multi-Task Representation Learning towards Robust Online Budget Allocation
• Neural Topic Modeling by Incorporating Document Relationship Graph
• Powerpropagation: A sparsity inducing weight reparameterisation
• LoRA as a Flexible Framework for Securing Large Vision Systems
• Differential privacy for medical deep learning: methods, tradeoffs, and deployment implications
• Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification
• Channel Normalization for Time Series Channel Identification
• Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes
• Resource-Efficient Neural Networks for Embedded Systems
• An Effective Hit-or-Miss Layer Favoring Feature Interpretation as Learned Prototypes Deformations
• Interpretable agent communication from scratch (with a generic visual processor emerging on the side)
• Spectrum Attention Mechanism for Time Series Classification
• Graph-Based Object Classification for Neuromorphic Vision Sensing
• SSAP: Single-Shot Instance Segmentation With Affinity Pyramid
• Batch Normalization Orthogonalizes Representations in Deep Random Networks
• CHIP: Chameleon Hash-based Irreversible Passport for Robust Deep Model Ownership Verification and Active Usage Control
• PROM: Prioritize Reduction of Multiplications Over Lower Bit-Widths for Efficient CNNs
• Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem
• Spectro-Temporal RF Identification using Deep Learning
• Rethinking Neural Combinatorial Optimization for Vehicle Routing Problems with Different Constraint Tightness Degrees
• MGFF-TDNN: A Multi-Granularity Feature Fusion TDNN Model with Depth-Wise Separable Module for Speaker Verification
• Multi-output Classification using a Cross-talk Architecture for Compound Fault Diagnosis of Motors in Partially Labeled Condition
• Semi Supervised Deep Quick Instance Detection and Segmentation
• Searching Neural Architectures for Sensor Nodes on IoT Gateways
• The Nonlinearity Coefficient - A Practical Guide to Neural Architecture Design
• Multi-Task Self-Supervised Pre-Training for Music Classification
• The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs with Hybrid Parallelism
• The Panaceas for Improving Low-Rank Decomposition in Communication-Efficient Federated Learning
• How far away are truly hyperparameter-free learning algorithms?
• Towards High Performance Human Keypoint Detection
• IDEAL: Independent Domain Embedding Augmentation Learning
• Fast Monte Carlo Dropout and Error Correction for Radio Transmitter Classification
• Rethinking Assumptions in Deep Anomaly Detection
• Point-MoE: Large-Scale Multi-Dataset Training with Mixture-of-Experts for 3D Semantic Segmentation
• Hybrid-graph neural network method for muon fast reconstruction in neutrino telescopes
• Automatic species identification from images for Aotearoa
• Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi's Entropy and Tensor Kernels
• State-Aware Rate Adaptation for UAVs by Incorporating On-Board Sensors
• TinaFace: Strong but Simple Baseline for Face Detection
• ID-aware Quality for Set-based Person Re-identification
• Efficient Reinforcement Learning for StarCraft by Abstract Forward Models and Transfer Learning
• GP: Context-free Grammar Pre-training for Text-to-SQL Parsers
• Rectangular Flows for Manifold Learning
• A Comprehensive Survey on Test-Time Adaptation Under Distribution Shifts
• Towards Understanding the Transferability of Deep Representations
• Learning in Compact Spaces with Approximately Normalized Transformer
• Deep Learning with Low Precision by Half-wave Gaussian Quantization
• Structure-aware scale-adaptive networks for cancer segmentation in whole-slide images
• RC-AutoCalib: An End-to-End Radar-Camera Automatic Calibration Network
• RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers
• BigDataBench: A Scalable and Unified Big Data and AI Benchmark Suite
• Expressive yet Efficient Feature Expansion with Adaptive Cross-Hadamard Products
• Hybrid Batch Normalisation: Resolving the Dilemma of Batch Normalisation in Federated Learning
• SeqMobile: A Sequence Based Efficient Android Malware Detection System Using RNN on Mobile Devices
• Source-free Domain Adaptation via Distributional Alignment by Matching Batch Normalization Statistics
• Relevance-driven Input Dropout: an Explanation-guided Regularization Technique
• Characterizing the Reynolds number dependence of the chaotic attractor in two-dimensional turbulence with dimension-minimizing autoencoders
• No-regret Non-convex Online Meta-Learning
• Identifying Super Spreaders in Multilayer Networks
• Estimating Commonsense Scene Composition on Belief Scene Graphs
• Sharpness-Aware Minimization with Z-Score Gradient Filtering
• Unpaired Image-to-Image Translation for Segmentation and Signal Unmixing
• Detecting Informative Channels: ActionFormer
• Identifying and Exploiting Structures for Reliable Deep Learning
• Spiking Deep Residual Network
• Abstractive Text Classification Using Sequence-to-convolution Neural Networks
• Simulation-based Lidar Super-resolution for Ground Vehicles
• Deep unfolding as iterative regularization for imaging inverse problems
• Human Vocal Sentiment Analysis
• Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks
• Multiple Descents in Deep Learning as a Sequence of Order-Chaos Transitions
• OCN: Effectively Utilizing Higher-Order Common Neighbors for Better Link Prediction
• Regularization Methods for Generative Adversarial Networks: An Overview of Recent Studies
• Mosaic: Data-Free Knowledge Distillation via Mixture-of-Experts for Heterogeneous Distributed Environments
• Dual Encoder Fusion U-Net (DEFU-Net) for Cross-manufacturer Chest X-ray Segmentation
• Detecting cognitive impairments by agreeing on interpretations of linguistic features
• H-VECTORS: Utterance-level Speaker Embedding Using A Hierarchical Attention Model
• Frustratingly Easy Person Re-Identification: Generalizing Person Re-ID in Practice
• CA3D: Convolutional-Attentional 3D Nets for Efficient Video Activity Recognition on the Edge
• Scaling Properties of Deep Residual Networks
• Advancing Constrained Monotonic Neural Networks: Achieving Universal Approximation Beyond Bounded Activations
• Overcoming Difficulty in Obtaining Dark-skinned Subjects for Remote-PPG by Synthetic Augmentation
• Translation-Equivariance of Normalization Layers and Aliasing in Convolutional Neural Networks
• Automated ECG classification using a non-local convolutional block attention module
• End-to-End Bengali Speech Recognition
• Single-Stage 6D Object Pose Estimation
• AdaSample: Adaptive Sampling of Hard Positives for Descriptor Learning
• Object-Oriented Dynamics Learning through Multi-Level Abstraction
• Pillar-based Object Detection for Autonomous Driving
• Supervized Segmentation with Graph-Structured Deep Metric Learning
• RAISE: Realness Assessment for Image Synthesis and Evaluation
• Weight Evolution: Improving Deep Neural Networks Training through Evolving Inferior Weight Values
• The Break-Even Point on Optimization Trajectories of Deep Neural Networks
• Path Aggregation Network for Instance Segmentation
• Deep Metric Learning with Spherical Embedding
• DcaseNet: An integrated pretrained deep neural network for detecting and classifying acoustic scenes and events
• Meta Pruning via Graph Metanetworks : A Universal Meta Learning Framework for Network Pruning
• Joint-stochastic-approximation Random Fields with Application to Semi-supervised Learning
• Heavily Augmented Sound Event Detection utilizing Weak Predictions
• Cross Attention Network for Semantic Segmentation
• Learning Optimal Conformal Classifiers
• Leveraging KANs for Expedient Training of Multichannel MLPs via Preconditioning and Geometric Refinement
• Beyond Discreteness: Finite-Sample Analysis of Straight-Through Estimator for Quantization
• Bayesian Deep Learning for Discrete Choice
• Spatiotemporal CNN for Video Object Segmentation
• Convolutional Auto-encoding of Sentence Topics for Image Paragraph Generation
• Reducing Geographic Performance Differential for Face Recognition
• Centripetal SGD for Pruning Very Deep Convolutional Networks with Complicated Structure
• Towards Deeper Deep Reinforcement Learning with Spectral Normalization
• Searching for Low-Bit Weights in Quantized Neural Networks
• Generative Learning With Euler Particle Transport
• HiLAB: A Hybrid Inverse-Design Framework
• AlignSeg: Feature-Aligned Segmentation Networks
• Hierarchical Representation Network for Steganalysis of QIM Steganography in Low-Bit-Rate Speech Signals
• Context-Gated Convolution
• TransLoc3D : Point Cloud based Large-scale Place Recognition using Adaptive Receptive Fields
• CycleMLP: A MLP-like Architecture for Dense Prediction
• Region-based Quality Estimation Network for Large-scale Person Re-identification
• Over Parameterized Two-level Neural Networks Can Learn Near Optimal Feature Representations
• Divisive Normalization Shapes Low-Rank Slow Manifolds for Continuous Working Memory
• DDR-ID: Dual Deep Reconstruction Networks Based Image Decomposition for Anomaly Detection
• The Local Elasticity of Neural Networks
• TULiP: Test-time Uncertainty Estimation via Linearization and Weight Perturbation
• Interleaved Multitask Learning for Audio Source Separation with Independent Databases
• Encrypted Speech Recognition using Deep Polynomial Networks
• Spherical Motion Dynamics: Learning Dynamics of Neural Network with Normalization, Weight Decay, and SGD
• Joint Transmission Map Estimation and Dehazing using Deep Networks
• From Image to Imuge: Immunized Image Generation
• BitSplit-Net: Multi-bit Deep Neural Network with Bitwise Activation Function
• Higher-Order Asymptotics of Test-Time Adaptation for Batch Normalization Statistics
• An Empirical Study of Graph Contrastive Learning
• Auto-nnU-Net: Towards Automated Medical Image Segmentation
• Torchreid: A Library for Deep Learning Person Re-Identification in Pytorch
• An ETF view of Dropout regularization
• Synthesis of Ventilator Dyssynchrony Waveforms using a Hybrid Generative Model and a Lung Model
• Interpretable and Accurate Fine-grained Recognition via Region Grouping
• Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks
• Bayesian Optimization with Approximate Set Kernels
• MHANet: Multi-scale Hybrid Attention Network for Auditory Attention Detection
• Machine Learning based Soil VWC and Field Capacity Estimation Using Low Cost Sensors
• Edge-Labeling based Directed Gated Graph Network for Few-shot Learning
• Meta-Learning with Warped Gradient Descent
• Reconstruction Bottlenecks in Object-Centric Generative Models
• Accelerating Deep Unsupervised Domain Adaptation with Transfer Channel Pruning
• Convolutional Neural Network-based Intrusion Detection System for AVTP Streams in Automotive Ethernet-based Networks
• SA-GD: Improved Gradient Descent Learning Strategy with Simulated Annealing
• Integration of TinyML and LargeML: A Survey of 6G and Beyond
• Explaining Neural Networks with Reasons
• ThinkSwitcher: When to Think Hard, When to Think Fast
• 3D Shape Synthesis for Conceptual Design and Optimization Using Variational Autoencoders
• Learning to Insert for Constructive Neural Vehicle Routing Solver
• A Large-Scale Study on Unsupervised Spatiotemporal Representation Learning
• Are Nearby Neighbors Relatives?: Testing Deep Music Embeddings
• Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning
• Class-Distinct and Class-Mutual Image Generation with GANs
• Self Distillation via Iterative Constructive Perturbations
• Selective Structured State Space for Multispectral-fused Small Target Detection
• Parrotron: An End-to-End Speech-to-Speech Conversion Model and its Applications to Hearing-Impaired Speech and Speech Separation
• Partial transfusion: on the expressive influence of trainable batch norm parameters for transfer learning
• A Coarse-to-Fine Adaptive Network for Appearance-Based Gaze Estimation
• Data-driven Weight Initialization with Sylvester Solvers
• Mixed-Supervised Dual-Network for Medical Image Segmentation
• Student Helping Teacher: Teacher Evolution via Self-Knowledge Distillation
• Deep Semi-Supervised Anomaly Detection
• Convolutional Networks with Dense Connectivity
• An Adaptive Empirical Bayesian Method for Sparse Deep Learning
• Recent Advances in Object Detection in the Age of Deep Convolutional Neural Networks
• Advancing Generalization Across a Variety of Abstract Visual Reasoning Tasks
• Towards Deeper Graph Neural Networks with Differentiable Group Normalization
• An Overview of Arithmetic Adaptations for Inference of Convolutional Neural Networks on Re-configurable Hardware
• Parallel Layer Normalization for Universal Approximation
• Machine learning the first stage in 2SLS: Practical guidance from bias decomposition and simulation
• Batch-Instance Normalization for Adaptively Style-Invariant Neural Networks
• EuLearn: A 3D database for learning Euler characteristics
• Quantized Neural Networks via -1, +1 Encoding Decomposition and Acceleration
• Distinguishing the activity of flexor digitorum brevis and soleus across standing postures with deep learning models
• Cross-scale Attention Model for Acoustic Event Classification
• Sound Event Detection of Weakly Labelled Data with CNN-Transformer and Automatic Threshold Optimization
• Towards Optimal Power Control via Ensembling Deep Neural Networks
• Learning Combinatorial Node Labeling Algorithms
• SchoenbAt: Rethinking Attention with Polynomial basis
• Deep Reinforcement Learning for Chatbots Using Clustered Actions and Human-Likeness Rewards
• Deep-learning based Tools for Automated Protocol Definition of Advanced Diagnostic Imaging Exams
• Tree-Augmented Cross-Modal Encoding for Complex-Query Video Retrieval
• Responsible AI: Gender bias assessment in emotion recognition
• A Training Framework for Optimal and Stable Training of Polynomial Neural Networks
• From Fibers to Cells: Fourier-Based Registration Enables Virtual Cresyl Violet Staining From 3D Polarized Light Imaging
• Fast contour propagation for MR‐guided prostate radiotherapy using convolutional neural networks
• Protein–protein and protein–nucleic acid binding site prediction via interpretable hierarchical geometric deep learning
• Towards a machine-learned Poisson solver for low-temperature plasma simulations in complex geometries
• Yet Another Intermediate-Level Attack
• Neighbor Oblivious Learning (NObLe) for Device Localization and Tracking
• Volume of hyperintense inflammation (VHI): a deep learning-enabled quantitative imaging biomarker of inflammation load in spondyloarthritis
• Spatio-Temporal Channel Correlation Networks for Action Classification
• VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis
• Activity Driven Weakly Supervised Object Detection
• A Multi-modal Fusion Network for Terrain Perception Based on Illumination Aware
• Holistic and Comprehensive Annotation of Clinically Significant Findings on Diverse CT Images: Learning from Radiology Reports and Label Ontology
• Decentralized Learning of Generative Adversarial Networks from Non-iid Data
• Coupled Generative Adversarial Network for Continuous Fine-grained Action Segmentation
• Veritatem Dies Aperit- Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach
• Recurrent Connectivity Aids Recognition of Partly Occluded Objects
• ROI Regularization for Semi-supervised and Supervised Learning
• Uniform Loss vs. Specialized Optimization: A Comparative Analysis in Multi-Task Learning
• Reconstructing the Plasma Boundary with a Reduced Set of Diagnostics
• Derivative Manipulation for General Example Weighting
• LCPNet: Latent Consistent Proximal Unfolding Network for Infrared Small Target Detection
• CSPENet: Contour-Aware and Saliency Priors Embedding Network for Infrared Small Target Detection
• Learning to Optimize Domain Specific Normalization for Domain Generalization
• Neural Multivariate Regression: Qualitative Insights from the Unconstrained Feature Model
• Variational Prefix Tuning for Diverse and Accurate Code Summarization Using Pre-trained Language Models
• Data-driven Cloud Clustering via a Rotationally Invariant Autoencoder
• Virtual Dosimetrists: A Radiotherapy Training "Flight Simulator"
• Robust Federated Learning with Confidence-Weighted Filtering and GAN-Based Completion under Noisy and Incomplete Data
• RF-HOI: Recognize Human-Object Interaction with Radio Frequency Signals
• I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively
• A Large-scale Benchmark on Geological Fault Delineation Models: Domain Shift, Training Dynamics, Generalizability, Evaluation and Inferential Behavior
• Don't ignore Dropout in Fully Convolutional Networks
• Take More Positives: An Empirical Study of Contrastive Learing in Unsupervised Person Re-Identification
• Deep Metric Learning by Online Soft Mining and Class-Aware Attention
• Automated airway segmentation by learning graphical structure
• GAN-based Pose-aware Regulation for Video-based Person Re-identification
• Improving Few-Shot Learning with Auxiliary Self-Supervised Pretext Tasks
• Normalized Attention Without Probability Cage
• Generative Deep Learning Techniques for Password Generation
• Unsupervised Raindrop Removal from a Single Image using Conditional Diffusion Models
• Low-Complexity Inference in Continual Learning via Compressed Knowledge Transfer
• Deep Interaction between Masking and Mapping Targets for Single-Channel Speech Enhancement
• Learning End-to-End Lossy Image Compression: A Benchmark
• Double Descent Optimization Pattern and Aliasing: Caveats of Noisy Labels
• Reliable Liver Fibrosis Assessment from Ultrasound using Global Hetero-Image Fusion and View-Specific Parameterization
• HMOR: Hierarchical Multi-Person Ordinal Relations for Monocular Multi-Person 3D Pose Estimation
• Modeling Uncertainty by Learning a Hierarchy of Deep Neural Connections
• Tagging fully hadronic exotic decays of the vectorlike B quark using a graph neural network
• TAB-VCR: Tags and Attributes based Visual Commonsense Reasoning Baselines
• Many-to-Many Voice Conversion using Cycle-Consistent Variational Autoencoder with Multiple Decoders
• Detecting Colorized Images via Convolutional Neural Networks: Toward High Accuracy and Good Generalization
• Wireless Link Scheduling with State-Augmented Graph Neural Networks
• CurlingNet: Compositional Learning between Images and Text for Fashion IQ Data
• Genome Variant Calling with a Deep Averaging Network
• ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction
• Robust Conditional Generative Adversarial Networks
• A connectome and analysis of the adult Drosophila central brain
• Neural Architecture Search for Lightweight Non-Local Networks
• Spherical Kernel for Efficient Graph Convolution on 3D Point Clouds
• AIBench: An Industry Standard Internet Service AI Benchmark Suite
• Federated Adversarial Domain Adaptation
• Survey of Filtered Approximate Nearest Neighbor Search over the Vector-Scalar Hybrid Data
• Mask-PINNs: Mitigating Internal Covariate Shift in Physics-Informed Neural Networks
• Similarity-preserving Image-image Domain Adaptation for Person Re-identification
• Accurate and Efficient Multivariate Time Series Forecasting via Offline Clustering
• Document Image Rectification Bases on Self-Adaptive Multitask Fusion
• FIC-TSC: Learning Time Series Classification with Fisher Information Constraint
• DeepSync: A Learning Framework for Pervasive Localization using Code Synchronization on Compressed Cellular Spectrum
• AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights
• Boosting Statistic Learning with Synthetic Data from Pretrained Large Models
• Sparse Training from Random Initialization: Aligning Lottery Ticket Masks using Weight Symmetry
• Context Aware Machine Learning
• Hyperparameter Transfer Laws for Non-Recurrent Multi-Path Neural Networks
• Aligning Visual Prototypes with BERT Embeddings for Few-Shot Learning
• Wide & Deep Learning for Node Classification
• Time Matters in Regularizing Deep Networks: Weight Decay and Data Augmentation Affect Early Learning Dynamics, Matter Little Near Convergence
• Multimodal Machine Learning: A Survey and Taxonomy
• Video Representation Learning by Dense Predictive Coding
• Lattice Fusion Networks for Image Denoising
• Discovering Neural Wirings
• Improving Graph Neural Network Representations of Logical Formulae with Subgraph Pooling
• HiLLIE: Human-in-the-Loop Training for Low-Light Image Enhancement
• Local Herb Identification Using Transfer Learning: A CNN-Powered Mobile Application for Nepalese Flora
• q-Neurons: Neuron Activations based on Stochastic Jackson's Derivative Operators
• Training Energy-Efficient Deep Spiking Neural Networks with Time-to-First-Spike Coding
• Dendritic Computing with Multi-Gate Ferroelectric Field-Effect Transistors
• Speech and Speaker Recognition from Raw Waveform with SincNet
• Deep-3DAligner: Unsupervised 3D Point Set Registration Network With Optimizable Latent Vector
• On the Role of Optimization in Double Descent: A Least Squares Study
• Deep learning for automatic tumour segmentation in PET/CT images of patients with head and neck cancers
• ConvS2S-VC: Fully convolutional sequence-to-sequence voice conversion
• Efficient Vision-based Vehicle Speed Estimation
• InGAN: Capturing and Remapping the "DNA" of a Natural Image
• LCP: A Low-Communication Parallelization Method for Fast Neural Network Inference in Image Recognition
• Orthogonal Over-Parameterized Training
• Relation-Shape Convolutional Neural Network for Point Cloud Analysis
• What Deep CNNs Benefit from Global Covariance Pooling: An Optimization Perspective
• Pipelined Backpropagation at Scale: Training Large Models without Batches
• KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation
• Adaptive Task Sampling for Meta-Learning
• Low-Precision Training of Large Language Models: Methods, Challenges, and Opportunities
• On Random Kernels of Residual Architectures
• A Neural Architecture Search Method using Auxiliary Evaluation Metric based on ResNet Architecture
• Reflection-based Word Attribute Transfer
• Scalable and Practical Natural Gradient for Large-Scale Deep Learning
• AdderNet and its Minimalist Hardware Design for Energy-Efficient Artificial Intelligence
• Utilising Gradient-Based Proposals Within Sequential Monte Carlo Samplers for Training of Partial Bayesian Neural Networks
• On the Importance of Gaussianizing Representations
• A Neural Text-to-Speech Model Utilizing Broadcast Data Mixed with Background Music
• Finding and Visualizing Weaknesses of Deep Reinforcement Learning Agents
• Improving Sound Event Classification by Increasing Shift Invariance in Convolutional Neural Networks
• Deep Multi-task Learning for Facial Expression Recognition and Synthesis Based on Selective Feature Sharing
• Scene Graph Generation for Better Image Captioning?
• SDGMNet: Statistic-based Dynamic Gradient Modulation for Local Descriptor Learning
• Inverse reinforcement learning for autonomous navigation via differentiable semantic mapping and planning
• Self-Supervised Learning by Estimating Twin Class Distributions
• LiStereo: Generate Dense Depth Maps from LIDAR and Stereo Imagery
• SNDCNN: Self-normalizing deep CNNs with scaled exponential linear units for speech recognition
• Joint Deep Cross-Domain Transfer Learning for Emotion Recognition
• Non-local U-Net for Biomedical Image Segmentation
• FOVI: A biologically-inspired foveated interface for deep vision models
• Trust-Region Algorithms for Training Responses: Machine Learning Methods\n Using Indefinite Hessian Approximations
• Sphere Retraction Normalizations
• Neural Wireframe Renderer: Learning Wireframe to Image Translations
• Dense Residual Network: Enhancing Global Dense Feature Flow for Character Recognition
• An initial attempt of combining visual selective attention with deep reinforcement learning
• Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible Evaluation
• Show and tell: A neural image caption generator
• Multi Voxel-Point Neurons Convolution (MVPConv) for Fast and Accurate 3D Deep Learning
• Convergence of Deep Fictitious Play for Stochastic Differential Games
• DeepFolio: Convolutional Neural Networks for Portfolios with Limit Order Book Data
• McKernel: A Library for Approximate Kernel Expansions in Log-linear Time
• Generative Wind Power Curve Modeling Via Machine Vision: A Self-learning Deep Convolutional Network Based Method
• Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation
• Unsupervised Visual Representation Learning by Context Prediction
• SOAR: Second-Order Adversarial Regularization
• Efficient Saliency Maps for Explainable AI
• Compression based bound for non-compressed network: unified generalization error analysis of large compressible deep neural network
• From inference to prediction: how machine learning is reconfiguring science
• Neuron with Steady Response Leads to Better Generalization
• Towards Defending Multiple ℓ_p-norm Bounded Adversarial Perturbations via Gated Batch Normalization
• NVAE: A Deep Hierarchical Variational Autoencoder
• Generalizing MLPs With Dropouts, Batch Normalization, and Skip Connections
• Efficient Training Convolutional Neural Networks on Edge Devices with Gradient-pruned Sign-symmetric Feedback Alignment
• iMacHSR: Intermediate Multi-Access Heterogeneous Supervision and Regularization Scheme Toward Architecture-Agnostic Training
• SBSGAN: Suppression of Inter-Domain Background Shift for Person Re-Identification
• Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases
• Multi-stage domain adversarial style reconstruction for cytopathological image stain normalization
• Large-Scale Generative Data-Free Distillation
• Exploring Semantic Segmentation on the DCT Representation
• Non-local Neural Networks
• An end to end Deep Neural Network for iris segmentation in unconstrained scenarios
• Estimating the Robustness of Classification Models by the Structure of the Learned Feature-Space
• End-to-End Unsupervised Deformable Image Registration with a Convolutional Neural Network
• Iterative Normalization: Beyond Standardization towards Efficient Whitening
• Feature Correlation Aggregation: on the Path to Better Graph Neural Networks
• Template-Instance Loss for Offline Handwritten Chinese Character Recognition
• Hierarchical Recurrent Attention Networks for Structured Online Maps
• Speaker Diarization Using Deep Recurrent Convolutional Neural Networks for Speaker Embeddings
• Interpreting Spatially Infinite Generative Models
• Putting 3D Spatially Sparse Networks on a Diet
• Portraying double Higgs at the Large Hadron Collider
• Multi-modal anticipation of stochastic trajectories in a dynamic environment with Conditional Variational Autoencoders
• Powder-Bed Fusion Process Monitoring by Machine Vision With Hybrid Convolutional Neural Networks
• Image Generation with a Sphere Encoder
• Deep Learning Forecasting of the U.S. Aggregate Bond Index
• xEEGNet: Towards Explainable AI in EEG Dementia Classification
• A Memetic Algorithm based on Variational Autoencoder for Black-Box Discrete Optimization with Epistasis among Parameters
• Pion: A Spectrum-Preserving Optimizer via Orthogonal Equivalence Transformation
• On Connections between Regularizations for Improving DNN Robustness
• Efficient Listener: Dyadic Facial Motion Synthesis via Action Diffusion
• Learning Streaming Video Representation via Multitask Training
• Towards Universal Spatial Transcriptomics Super-Resolution: A Generalist Physically Consistent Flow Matching Framework
• Stabilizing In-Context Multi-Source Domain Adaptation for Biomedical Images Through Controls
• Physics-informed, Generative Adversarial Design of Funicular Shells
• TreeON: Reconstructing 3D Tree Point Clouds from Orthophotos and Heightmaps
• Lightweight Adapter Learning for More Generalized Remote Sensing Change Detection
• Distillation-based fabric anomaly detection
• BQSched: A Non-intrusive Scheduler for Batch Concurrent Queries via Reinforcement Learning
• Performance Study of a Position-sensitive Plastic Scintillator Detector
• Deep Learning vs. Black-Scholes: Option Pricing Performance on Brazilian Petrobras Stocks
• UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-identification in Video Imagery
• On Multitask Loss Function for Audio Event Detection and Localization
• Dual-CyCon Net: A Cycle Consistent Dual-Domain Convolutional Neural Network Framework for Detection of Partial Discharge
• Domain Adaptation and Active Learning for Fine-Grained Recognition in the Field of Biodiversity
• Parallel Training of Deep Networks with Local Updates
• Deep bilateral learning for real-time image enhancement
• Deep learning for time series classification
• Improved Selective Refinement Network for Face Detection
• Learning by Turning: Neural Architecture Aware Optimisation
• OrbNet: Deep Learning for Quantum Chemistry Using Symmetry-Adapted Atomic-Orbital Features
• Graph Neural Network Reveals the Cortical Morphology of Local Brain Aging in Normal Cognition and Alzheimer's Disease
• Coupled Recurrent Network (CRN)
• Learning Eye-in-Hand Camera Calibration from a Single Image
• XiDepth: a Lightweight and Efficient Network for Self-supervised Monocular Depth Estimation
• In-Loop Meta-Learning with Gradient-Alignment Reward
• Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness
• A Novel Sleep Stage Classification Using CNN Generated by an Efficient Neural Architecture Search with a New Data Processing Trick
• Luminance Attentive Networks for HDR Image and Panorama Reconstruction
• On the use of case estimate and transactional payment data in neural networks for individual loss reserving
• A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis
• Image Generation From Small Datasets via Batch Statistics Adaptation
• STM: SpatioTemporal and Motion Encoding for Action Recognition
• Few-Shot Learning with Global Class Representations
• Learning deep spatiotemporal features for video captioning
• Partition Map-Based Fast Block Partitioning for VVC Inter Coding
• LaundroGraph: Self-Supervised Graph Representation Learning for Anti-Money Laundering
• HydroStartML: A combined machine learning and physics-based approach to reduce hydrological model spin-up time
• CANet: ChronoAdaptive Network for Enhanced Long-Term Time Series Forecasting under Non-Stationarity
• Application of an attention-based CNN-BiLSTM framework for in vivo two-photon calcium imaging of neuronal ensembles: decoding complex bilateral forelimb movements from unilateral M1
• ShuffleBlock: Shuffle to Regularize Deep Convolutional Neural Networks
• Incorporating Multi-Target in Multi-Stage Speech Enhancement Model for Better Generalization
• Neural Networks Versus Conventional Filters for Inertial-Sensor-based Attitude Estimation
• The Neural Echo: A Signal Processing Perspective for Understanding Neural Networks
• Cross-sectional Stock Price Prediction using Deep Learning for Actual Investment Management
• Stampnet: Unsupervised Multi-Class Object Discovery
• Music Artist Classification with Convolutional Recurrent Neural Networks
• A deep learning approach for pose estimation from volumetric OCT data
• Learning to Represent and Predict Sets with Deep Neural Networks
• Probabilistic Vehicle Reconstruction Using a Multi-Task CNN
• Efficient Certified Defenses Against Patch Attacks on Image Classifiers
• Numerical Calabi-Yau metrics from holomorphic networks
• Spectrum Correction: Acoustic Scene Classification with Mismatched Recording Devices
• On Filter Generalization for Music Bandwidth Extension Using Deep Neural Networks
• Swapping Autoencoder for Deep Image Manipulation
• A Flexible Selection Scheme for Minimum-Effort Transfer Learning
• Spatially regularized parametric map reconstruction for fast magnetic resonance fingerprinting
• Link Prediction on N-ary Relational Data Based on Relatedness Evaluation
• Mathematical Model and Simulation for Nutrient-Plant Interaction Analysis
• DeepMTL Pro: Deep Learning Based MultipleTransmitter Localization and Power Estimation
• Recent Progress in the CUHK Dysarthric Speech Recognition System
• Using fuzzy bits and neural networks to partially invert few rounds of some cryptographic hash functions
• Towards Amortized Ranking-Critical Training for Collaborative Filtering
• A Novel Graph Transformer Framework for Gene Regulatory Network Inference
• Revisiting Radar Camera Alignment by Contrastive Learning for 3D Object Detection
• Fried Parameter Estimation from Single Wavefront Sensor Image with Artificial Neural Networks
• Multi-Task Learning With Coarse Priors for Robust Part-Aware Person Re-Identification
• FedHealth 2: Weighted Federated Transfer Learning via Batch Normalization for Personalized Healthcare
• A Comparison for Patch-level Classification of Deep Learning Methods on Transparent Environmental Microorganism Images: from Convolutional Neural Networks to Visual Transformers
• Online Adaptation through Meta-Learning for Stereo Depth Estimation
• Infrared and 3D Skeleton Feature Fusion for RGB-D Action Recognition
• Compensating for visibility artefacts in photoacoustic imaging with a deep learning approach providing prediction uncertainties
• Design of metalloproteins and novel protein folds using variational autoencoders
• Deep Gated Recurrent and Convolutional Network Hybrid Model for Univariate Time Series Classification
• Deep Unsupervised Learning for Joint Antenna Selection and Hybrid Beamforming
• Deep triplet hashing network for case-based medical image retrieval
• Knowledge Guided Disambiguation for Large-Scale Scene Classification With Multi-Resolution CNNs
• Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology
• Adversarial Attacks on Deep Neural Networks for Time Series Classification
• A Generative Adversarial Network for AI-Aided Chair Design
• Building medical image classifiers with very limited data using segmentation networks
• Temporal Sequence Distillation
• SiTGRU: Single-Tunnelled Gated Recurrent Unit for Abnormality Detection
• Complex-valued neural networks for machine learning on non-stationary physical data
• Unsupervised Object Detection with LiDAR Clues
• Using convolutional neural networks to predict galaxy metallicity from three-colour images
• TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data
• On the impact of selected modern deep-learning techniques to the performance and celerity of classification models in an experimental high-energy physics use case
• Signal Combination for Language Identification
• Integration of Adversarial Autoencoders With Residual Dense Convolutional Networks for Estimation of Non‐Gaussian Hydraulic Conductivities
• Analytical Softmax Temperature Setting from Feature Dimensions for Model- and Domain-Robust Classification
• The Open Images Dataset V4
• Enabling Spike-Based Backpropagation for Training Deep Neural Network Architectures
• Convergence of the Deep BSDE Method for Coupled FBSDEs
• VeLU: Variance-enhanced Learning Unit for Deep Neural Networks
• How to systematically develop an effective AI-based bias correction model?
• A Basic Evaluation of Neural Networks Trained with the Error Diffusion Learning Algorithm
• Network Quantization with Element-wise Gradient Scaling
• Demonstration of background rejection using deep convolutional neural networks in the NEXT experiment
• Differentially Private Federated Learning for Resource-Constrained Internet of Things
• Removal of Batch Effects using Generative Adversarial Networks
• Rethinking Neural Operations for Diverse Tasks
• Multiperson Continuous Tracking and Identification From mm-Wave Micro-Doppler Signatures
• Acoustic Anomaly Detection for Machine Sounds based on Image Transfer Learning
• Temporal Network Representation Learning via Historical Neighborhoods Aggregation
• Unsupervised Learning of Depth, Optical Flow and Pose With Occlusion From 3D Geometry
• Deep neural network for solving differential equations motivated by Legendre-Galerkin approximation
• Multi-Level Attention Pooling for Graph Neural Networks: Unifying Graph Representations with Multiple Localities
• Ensemble Kalman inversion: a derivative-free technique for machine learning tasks
• Action Shuffling for Weakly Supervised Temporal Localization
• Learning to Set Waypoints for Audio-Visual Navigation
• DoFE: Domain-Oriented Feature Embedding for Generalizable Fundus Image Segmentation on Unseen Datasets
• Quasi-hyperbolic momentum and Adam for deep learning
• CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive Survey
• Performance of a deep neural network at detecting North Atlantic right whale upcalls
• An Artificial Intelligence Enabled Signature Estimation of Dual Wideband Systems in Ultra-Low Signal-to-Noise Ratio
• Segment Any Crack: Deep Semantic Segmentation Adaptation for Crack Detection
• Scaling LLaNA: Advancing NeRF-Language Understanding Through Large-Scale Training
• Generative Parameter Sampler For Scalable Uncertainty Quantification
• KAN or MLP? Point Cloud Shows the Way Forward
• A Comparison of Neural Network Architectures for Data-Driven Reduced-Order Modeling
• Deep Self-Supervised Representation Learning for Free-Hand Sketch
• Fully automated organ segmentation in male pelvic CT images
• Decentralised Person Re-Identification with Selective Knowledge Aggregation
• Weak-lensing Mass Reconstruction of Galaxy Clusters with a Convolutional Neural Network
• Scattering Networks for Hybrid Representation Learning
• Ellipse R-CNN: Learning to Infer Elliptical Object From Clustering and Occlusion
• On-device Filtering of Social Media Images for Efficient Storage
• DSIC: Deep Stereo Image Compression
• Improving Sequential Latent Variable Models with Autoregressive Flows
• Stratify: Rethinking Federated Learning for Non-IID Data through Balanced Sampling
• Artistic Style Transfer for Videos and Spherical Images
• Scaling Object Detection by Transferring Classification Weights
• Deep Ensembles on a Fixed Memory Budget: One Wide Network or Several Thinner Ones?
• Guided Anisotropic Diffusion and Iterative Learning for Weakly\n Supervised Change Detection
• CG-Net: Conditional GIS-aware Network for Individual Building Segmentation in VHR SAR Images
• Learning Without Feedback: Fixed Random Learning Signals Allow for Feedforward Training of Deep Neural Networks
• Learning Class-Specific Features with Class Regularization for Videos
• An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods
• DeFMO: Deblurring and Shape Recovery of Fast Moving Objects
• Convolutional Recurrent Neural Network Based Progressive Learning for Monaural Speech Enhancement
• Extracting the Subhalo Mass Function from Strong Lens Images with Image Segmentation
• Viscos Flows: Variational Schur Conditional Sampling With Normalizing Flows
• CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation
• Heterogeneous Multilayer Generalized Operational Perceptron
• Bilevel Online Adaptation for Out-of-Domain Human Mesh Reconstruction
• Decorrelated Adversarial Learning for Age-Invariant Face Recognition
• Memory-Based Graph Networks
• Using Anomaly Feature Vectors for Detecting, Classifying and Warning of Outlier Adversarial Examples
• Getting High: High Fidelity Simulation of High Granularity Calorimeters with High Speed
• Improvements to Context Based Self-Supervised Learning
• Jamming transition as a paradigm to understand the loss landscape of deep neural networks
• Learning Interpretable Concept Groups in CNNs
• AxonDeepSeg: automatic axon and myelin segmentation from microscopy data using convolutional neural networks
• Lookahead: A Far-Sighted Alternative of Magnitude-based Pruning
• Evolution of Image Segmentation using Deep Convolutional Neural Network: A Survey
• Magnetic Resonance Fingerprinting Reconstruction Using Recurrent Neural Networks
• Deep Learning for Scene Classification: A Survey
• Automatic Prediction of Building Age from Photographs
• SlowFast Networks for Video Recognition
• Environmental sound classification using convolution neural networks with different integrated loss functions
• Image Denoising using Attention-Residual Convolutional Neural Networks
• OmiEmbed: A Unified Multi-Task Deep Learning Framework for Multi-Omics Data
• Predicting Localized Primordial Star Formation with Deep Convolutional Neural Networks
• CNN-based MultiChannel End-to-End Speech Recognition for everyday home environments
• Trunk-Branch Ensemble Convolutional Neural Networks for Video-Based Face Recognition
• On Procedural Adversarial Noise Attack And Defense
• Learning to Match Distributions for Domain Adaptation
• Revisiting Light Field Rendering with Deep Anti-Aliasing Neural Network
• Comparison of Deep Reinforcement Learning and Model Predictive Control for Adaptive Cruise Control
• Hadamard product in deep learning: Introduction, Advances and Challenges
• Baryon acoustic oscillations reconstruction using convolutional neural networks
• Mirror, Mirror of the Flow: How Does Regularization Shape Implicit Bias?
• Otter: A Time-Aware, History-Conditioned Human Chess AI
• MirBot: A collaborative object recognition system for smartphones using convolutional neural networks
• Deep Mining External Imperfect Data for Chest X-ray Disease Screening
• Direct Multitype Cardiac Indices Estimation via Joint Representation and Regression Learning
• Multi-output Classification Framework and Frequency Layer Normalization for Compound Fault Diagnosis in Motor
• Scalable Transceiver Design for Multi-User Communication in FDD Massive MIMO Systems via Deep Learning
• Efficient Brain Tumor Segmentation Using a Dual-Decoder 3D U-Net with Attention Gates (DDUNet)
• REPA-E: Unlocking VAE for End-to-End Tuning with Latent Diffusion Transformers
• Continual learning for rotating machinery fault diagnosis with cross-domain environmental and operational variations
• Cross-Problem Parameter Transfer in Quantum Approximate Optimization Algorithm: A Machine Learning Approach
• Physics-informed machine learning for predicting the ballistic limit of whipple shields
• Quantifying uncertainty in machine learning on nuclear binding energy
• Boosting-inspired online learning with transfer for railway maintenance
• Seaweed-7B: Cost-Effective Training of Video Generation Foundation Model
• Deep Learning Meets Teleconnections: Improving S2S Predictions for European Winter Weather
• Towards Lower-Dose PET using Physics-Based Uncertainty-Aware Multimodal\n Learning with Robustness to Out-of-Distribution Data
• Predicting Temporal Sets with Deep Neural Networks
• Heterogeneous Attentions for Solving Pickup and Delivery Problem via Deep Reinforcement Learning
• Combining time-series and textual data for taxi demand prediction in event areas: A deep learning approach
• Find A Winning Sign: Sign Is All We Need to Win the Lottery
• Exploring Kernel Transformations for Implicit Neural Representations
• Normalization (machine learning) [wikipedia]
• Batch normalization [wikipedia]
• Vanishing gradient problem [wikipedia]
• Normalization (statistics) [wikipedia]
• Feature scaling [wikipedia]
• Glossary of artificial intelligence [wikipedia]

Discussions

• Batch Normalization: Accelerating Deep Network Training [pdf] [hn, 134 points, 38 comments]
• Batch Normalization: Accelerating Deep Network Training (2015) [hn, 1 points, 0 comments]
• Ioffe and Szegedy get 4.8% top-5 test on ImageNet(beating recent MSR result) [hn, 1 points, 0 comments]

Related

• Training Deep Neural Networks Without Batch Normalization
• Batch Normalization and the impact of batch structure on the behavior of deep convolution networks
• Unified Batch Normalization: Identifying and Alleviating the Feature Condensation in Batch Normalization and a Unified Framework
• Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks
• How Does Batch Normalization Help Optimization?