The Graph Neural Network Model

2009/01/01 by F. Scarselli, M. Gori, Ah Chung Tsoi +2 · 301 citations

paper · doi:10.1109/tnn.2008.2005605

Cited by

• Generalization of Graph Neural Network Models for Distribution Grid Fault Detection
• Improving Human-Robot Teamwork in Urban Search and Rescue Through Episodic Memory of Prior Collaboration
• Symbol-Equivariant Recurrent Reasoning Models
• Inferring the Turbulent Breakup of Colloidal Aggregates Using Graph Neural Networks
• AI-assisted metaphotonics
• A roadmap for curvature-based geometric data analysis and learning
• Pedagogy-driven Evaluation of Generative AI-powered Intelligent Tutoring Systems
• Dynamic Graph Neural Network for Data-Driven Physiologically Based Pharmacokinetic Modeling
• On Local Limits of Sparse Random Graphs: Color Convergence and the Refined Configuration Model
• Sensing Without Colocation: Operator-Based Virtual Instrumentation for Domains Beyond Physical Reach
• QINNs: Quantum-Informed Neural Networks
• Inferred global dense residue transition graphs from primary structure sequences enable protein interaction prediction via directed graph convolutional neural networks
• GammaZero: Learning To Guide POMDP Belief Space Search With Graph Representations
• Axial Neural Networks for Dimension-Free Foundation Models
• Message Passing on the Edge: Towards Scalable and Expressive GNNs
• The Price-Pareto growth model of networks with community structure
• AGNES: Adaptive Graph Neural Network and Dynamic Programming Hybrid Framework for Real-Time Nanopore Seed Chaining
• A Matter of Representation: Towards Graph-Based Abstract Code Generation
• iCodeReviewer: Improving Secure Code Review with Mixture of Prompts
• A Comprehensive Survey of Website Fingerprinting Attacks and Defenses in Tor: Advances and Open Challenges
• Fast and the Furious: Hot Starts in Pursuit-Evasion Games
• Structure Over Signal: A Globalized Approach to Multi-relational GNNs for Stock Prediction
• A Graph-Attentive LSTM Model for Malicious URL Detection
• dN/dx Reconstruction with Deep Learning for High-Granularity TPCs
• On the Rademacher Complexity of Graph Neural Networks: Unifying Expressivity and Geometry
• gLSTM: Mitigating Over-Squashing by Increasing Storage Capacity
• MMM: Quantum-Chemical Molecular Representation Learning for Combinatorial Drug Recommendation
• DGTEN: A Robust Deep Gaussian based Graph Neural Network for Dynamic Trust Evaluation with Uncertainty-Quantification Support
• The Unreasonable Effectiveness of Randomized Representations in Online Continual Graph Learning
• Benchmarking Fake Voice Detection in the Fake Voice Generation Arms Race
• MaNGO - Adaptable Graph Network Simulators via Meta-Learning
• Enhancing NMR Shielding Predictions of Atoms-in-Molecules Machine Learning Models with Neighborhood-Informed Representations
• Directional Sheaf Hypergraph Networks: Unifying Learning on Directed and Undirected Hypergraphs
• Fractional Heat Kernel for Semi-Supervised Graph Learning with Small Training Sample Size
• Digital Twins for Intelligent Intersections: A Literature Review
• Toward Uncertainty-Aware and Generalizable Neural Decoding for Quantum LDPC Codes
• On the Convergence and Size Transferability of Continuous-depth Graph Neural Networks
• Graph Neural Networks in Large Scale Wireless Communication Networks: Scalability Across Random Geometric Graphs
• Ultra-Reliable Risk-Aggregated Sum Rate Maximization via Model-Aided Deep Learning
• Architecturally Constrained Solutions to Ill-Conditioned Problems in QUBIC
• Boolean Satisfiability via Imitation Learning
• AlphaSAGE: Structure-Aware Alpha Mining via GFlowNets for Robust Exploration
• Beyond Softmax: A Natural Parameterization for Categorical Random Variables
• Community detection robustness of graph neural networks
• VN-EGNN: E(3)- and SE(3)-Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification
• Introducing Multimodal Paradigm for Learning Sleep Staging PSG via General-Purpose Model
• Enhancing Molecular Dipole Moment Prediction with Multitask Machine Learning
• Reversible GNS for Dissipative Fluids with Consistent Bidirectional Dynamics
• Task-Adaptive Parameter-Efficient Fine-Tuning for Weather Foundation Models
• Rebuild AC Power Flow Models with Graph Attention Networks
• GraphUniverse: Synthetic Graph Generation for Evaluating Inductive Generalization
• Wonder Wins Ways: Curiosity-Driven Exploration through Multi-Agent Contextual Calibration
• Graph Variate Neural Networks
• Frame-based Equivariant Diffusion Models for 3D Molecular Generation
• SR2P: an efficient stacking method to predict protein abundance from gene expression in spatial transcriptomics data
• MSGAT-GRU: A Multi-Scale Graph Attention and Recurrent Model for Spatiotemporal Road Accident Prediction
• Quantum Graph Attention Network: A Novel Quantum Multi-Head Attention Mechanism for Graph Learning
• Learn to Rank Risky Investors: A Case Study of Predicting Retail Traders' Behaviour and Profitability
• Automated Cyber Defense with Generalizable Graph-based Reinforcement Learning Agents
• Beyond Words: Enhancing Desire, Emotion, and Sentiment Recognition with Non-Verbal Cues
• Accelerating Atomic Fine Structure Determination with Graph Reinforcement Learning
• Gumbel-MPNN: Graph Rewiring with Gumbel-Softmax
• How Bad Is Forming Your Own Multidimensional Opinion?
• Mixture of Low-Rank Adapter Experts in Generalizable Audio Deepfake Detection
• An End-to-End Differentiable, Graph Neural Network-Embedded Pore Network Model for Permeability Prediction
• Spatiotemporal graph neural process for reconstruction, extrapolation, and classification of cardiac trajectories
• Zero-shot Graph Reasoning via Retrieval Augmented Framework with LLMs
• Curvature as a tool for evaluating dimensionality reduction and estimating intrinsic dimension
• Learning from Heterophilic Graphs: A Spectral Theory Perspective on the Impact of Self-Loops and Parallel Edges
• Anomaly Detection in Industrial Control Systems Based on Cross-Domain Representation Learning
• Cluster Models for Next-Generation, Machine-Learning-Based Energy Functions for Molecular Simulations
• A neural drift-plus-penalty algorithm for network power allocation and routing
• Improving Greenland Bed Topography Mapping with Uncertainty-Aware Graph Learning on Sparse Radar Data
• Multimodal Contrastive Pretraining of CBCT and IOS for Enhanced Tooth Segmentation
• Long-Range Graph Wavelet Networks
• PAC-Bayesian Generalization Bounds for Graph Convolutional Networks on Inductive Node Classification
• Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks
• Data-Efficient Time-Dependent PDE Surrogates: Graph Neural Simulators vs. Neural Operators
• Multi-Stage Graph Neural Networks for Data-Driven Prediction of Natural Convection in Enclosed Cavities
• Learning to accelerate distributed ADMM using graph neural networks
• Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework
• Graph Unlearning: Efficient Node Removal in Graph Neural Networks
• AnomalyLMM: Bridging Generative Knowledge and Discriminative Retrieval for Text-Based Person Anomaly Search
• Error analysis for learning the time-stepping operator of evolutionary PDEs
• KGBERT4Eth: A Feature-Complete Transformer Powered by Knowledge Graph for Multi-Task Ethereum Fraud Detection
• Covariate Adjustment Cannot Hurt: Treatment Effect Estimation under Interference with Low-Order Outcome Interactions
• Learning Particle Dynamics Subject to Rigid Body Manipulations Using Graph Neural Networks
• MAUSAM: An Observations-focused assessment of Global AI Weather Prediction Models During the South Asian Monsoon
• Learn to Jump: Adaptive Random Walks for Long-Range Propagation through Graph Hierarchies
• Curriculum Guided Personalized Subgraph Federated Learning
• GraphKV: Breaking the Static Selection Paradigm with Graph-Based KV Cache Eviction
• A Geometric Perspective on the Difficulties of Learning GNN-based SAT Solvers
• Scalable Equilibrium Propagation via Intermediate Error Signals for Deep Convolutional CRNNs
• The Coherent Multiplex: Scalable Real-Time Wavelet Coherence Architecture
• Memorization in Graph Neural Networks
• VISION: Robust and Interpretable Code Vulnerability Detection Leveraging Counterfactual Augmentation
• A Machine Learning Approach to Volumetric Computations of Solid Pulmonary Nodules
• Fast Graph Neural Network for Image Classification
• Accelerating Image Classification with Graph Convolutional Neural Networks using Voronoi Diagrams
• Multimodal Data Storage and Retrieval for Embodied AI: A Survey
• DegDiT: Controllable Audio Generation with Dynamic Event Graph Guided Diffusion Transformer
• A Fully Spectral Neuro-Symbolic Reasoning Architecture with Graph Signal Processing as the Computational Backbone
• BLIPs: Bayesian Learned Interatomic Potentials
• A Neural-Network Framework for Tracking and Identification of Cosmic-Ray Nuclei in the RadMap Telescope
• MuDRiC: Multi-Dialect Reasoning for Arabic Commonsense Validation
• Root Cause Analysis of Hydrogen Bond Separation in Spatio-Temporal Molecular Dynamics using Causal Models
• Hierarchical Graph Feature Enhancement with Adaptive Frequency Modulation for Visual Recognition
• AnatoMaskGAN: GNN-Driven Slice Feature Fusion and Noise Augmentation for Medical Semantic Image Synthesis
• Graph Learning via Logic-Based Weisfeiler-Leman Variants and Tabularization
• Reasoning in Computer Vision: Taxonomy, Models, Tasks, and Methodologies
• Centralized Permutation Equivariant Policy for Cooperative Multi-Agent Reinforcement Learning
• Estimating carbon pools in the shelf sea environment: reanalysis or model-informed machine learning?
• Over-Squashing in GNNs and Causal Inference of Rewiring Strategies
• Edge-Selector Model Applied for Local Search Neighborhood for Solving Vehicle Routing Problems
• Symmetry-Aware Transformer Training for Automated Planning
• GraphCoT-VLA: A 3D Spatial-Aware Reasoning Vision-Language-Action Model for Robotic Manipulation with Ambiguous Instructions
• HSA-Net: Hierarchical and Structure-Aware Framework for Efficient and Scalable Molecular Language Modeling
• A Graph Neural Network based on a Functional Topology Model: Unveiling the Dynamic Mechanisms of Non-Suicidal Self-Injury in Single-Channel EEG
• Hypergraph Neural Network with State Space Models for Node Classification
• Dual Signal Decomposition of Stochastic Time Series
• Learning Geometric-Aware Quadrature Rules for Functional Minimization
• Functional Connectivity Graph Neural Networks
• Multi-Stage Knowledge-Distilled VGAE and GAT for Robust Controller-Area-Network Intrusion Detection
• GFocal: A Global-Focal Neural Operator for Solving PDEs on Arbitrary Geometries
• The Ubiquitous Sparse Matrix-Matrix Products
• Efficient Morphology-Aware Policy Transfer to New Embodiments
• Online Continual Graph Learning
• Revisiting Deep Information Propagation: Fractal Frontier and Finite-size Effects
• Causality and Interpretability for Electrical Distribution System faults
• Skeleton-Guided Learning for Shortest Path Search
• Reliable Microservice Tail Latency Prediction via Decoupled Dual-Stream Learning and Gradient Modulation
• VAGPO: Vision-augmented Asymmetric Group Preference Optimization for Graph Routing Problems
• R²-CoD: Understanding Text-Graph Complementarity in Relational Reasoning via Knowledge Co-Distillation
• Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks
• Superconductivity in atom-intercalated quaternary hydrides under ambient pressure
• Light-Weight Diffusion Multiplier and Uncertainty Quantification for Fourier Neural Operators
• MPFSR-Enhanced GNNs: Spectral Graph Neural Networks Enhancement Through Learnable Multiple-Parameter Graph Fractional Fourier Transforms
• TrajLens: Visual Analysis for Constructing Cell Developmental Trajectories in Cross-Sample Exploration
• HGCN(O): A Self-Tuning GCN HyperModel Toolkit for Outcome Prediction in Event-Sequence Data
• PINN and GNN-based RF Map Construction for Wireless Communication Systems
• Boosting Team Modeling through Tempo-Relational Representation Learning
• Air Traffic Controller Task Demand via Graph Neural Networks: An Interpretable Approach to Airspace Complexity
• Attributed Graph Clustering with Multi-Scale Weight-Based Pairwise Coarsening and Contrastive Learning
• BioNeuralNet: A Graph Neural Network based Multi-Omics Network Data Analysis Tool
• PIVOTS: Aligning unseen Structures using Preoperative to Intraoperative Volume-To-Surface Registration for Liver Navigation
• Improving Subgraph Matching by Combining Algorithms and Graph Neural Networks
• KD-GAT: Combining Knowledge Distillation and Graph Attention Transformer for a Controller Area Network Intrusion Detection System
• Doubling Your Data in Minutes: Ultra-fast Tabular Data Generation via LLM-Induced Dependency Graphs
• Financial Regulation and AI: A Faustian Bargain?
• Logical Characterizations of GNNs with Mean Aggregation
• Resolving Indirect Calls in Binary Code via Cross-Reference Augmented Graph Neural Networks
• Research on the application of graph data structure and graph neural network in node classification/clustering tasks
• C-DOG: Multi-View Multi-instance Feature Association Using Connected δ-Overlap Graphs
• Target Circuit Matching in Large-Scale Netlists using GNN-Based Region Prediction
• Binarizing Physics-Inspired GNNs for Combinatorial Optimization
• Physics-informed, boundary-constrained Gaussian process regression for the reconstruction of fluid flow fields
• Causal Process Models: Reframing Dynamic Causal Graph Discovery as a Reinforcement Learning Problem
• Tri-Learn Graph Fusion Network for Attributed Graph Clustering
• A Survey of Deep Learning for Geometry Problem Solving
• HyperEvent: A Strong Baseline for Dynamic Link Prediction via Relative Structural Encoding
• Foram3D: A pipeline for 3D synthetic data generation and rendering of foraminifera for image analysis and reconstruction
• SuperMetal: a generative AI framework for rapid and precise metal ion location prediction in proteins
• Shared Modular Recurrence in Contextual MDPs for Universal Morphology Control
• Assessing the Generalization of Graph Neural Networks for Fault Location Across Increasing Distributed Energy Resource Penetration Levels
• Bridging the Plausibility-Validity Gap by Fine-Tuning a Reasoning-Enhanced LLM for Chemical Synthesis and Discovery
• Generalization in Reinforcement Learning for Radio Access Networks
• SILVA Networks as Structured Implicit Layers and Vector Attractors via Dynamic Interaction Fields
• Learnable quantum spectral filters for hybrid graph neural networks
• Conditional Graph Neural Network for Predicting Soft Tissue Deformation and Forces
• Explainable Hierarchical Deep Learning Neural Networks (Ex-HiDeNN)
• PRING: Rethinking Protein-Protein Interaction Prediction from Pairs to Graphs
• High Order Collaboration-Oriented Federated Graph Neural Network for Accurate QoS Prediction
• Graph Neural Networks as a Substitute for Transformers in Single-Cell Transcriptomics
• Physics-Informed Graph Neural Networks to Reconstruct Local Fields Considering Finite Strain Hyperelasticity
• FAROS: Fair Graph Generation via Attribute Switching Mechanisms
• Structure-Aware Compound-Protein Affinity Prediction via Graph Neural Network with Group Lasso Regularization
• A Comprehensive Machine Learning Framework for Micromobility Demand Prediction
• MILP-SAT-GNN: Yet Another Neural SAT Solver
• Understanding Generalization in Node and Link Prediction
• Neural Augmented Kalman Filters for Road Network assisted GNSS positioning
• A New Perspective On AI Safety Through Control Theory Methodologies
• Quantum Graph Transformer for NLP Sentiment Classification
• Libra: Unleashing GPU Heterogeneity for High-Performance Sparse Matrix Multiplication
• FoGE: Fock Space inspired encoding for graph prompting
• Accelerating GNN Training through Locality-aware Dropout and Merge
• AGTCNet: A Graph-Temporal Approach for Principled Motor Imagery EEG Classification
• A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools
• Permutation Equivariant Neural Controlled Differential Equations for Dynamic Graph Representation Learning
• Efficient Extreme Operating Condition Search for Online Relay Setting Calculation in Renewable Power Systems Based on Parallel Graph Neural Network
• Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks
• A Brain-to-Population Graph Learning Framework for Diagnosing Brain Disorders
• EFormer: An Effective Edge-based Transformer for Vehicle Routing Problems
• Mitigating Over-Squashing in Graph Neural Networks by Spectrum-Preserving Sparsification
• Over-squashing in Spatiotemporal Graph Neural Networks
• A family of graph GOSPA metrics for graphs with different sizes
• Multi-Interest Recommendation: A Survey
• Language Embedding Meets Dynamic Graph: A New Exploration for Neural Architecture Representation Learning
• Quantum-Informed Contrastive Learning with Dynamic Mixup Augmentation for Class-Imbalanced Expert Systems
• Geometric Embedding Alignment via Curvature Matching in Transfer Learning
• MAGNet: A Multi-Scale Attention-Guided Graph Fusion Network for DRC Violation Detection
• Generalizable Trajectory Prediction via Inverse Reinforcement Learning with Mamba-Graph Architecture
• Directed Acyclic Graph Convolutional Networks
• Brain Network Analysis Based on Fine-tuned Self-supervised Model for Brain Disease Diagnosis
• How do Probabilistic Graphical Models and Graph Neural Networks Look at Network Data?
• SIMSHIFT: A Benchmark for Adapting Neural Surrogates to Distribution Shifts
• Graph Semi-Supervised Learning for Point Classification on Data Manifolds
• pLSTM: parallelizable Linear Source Transition Mark networks
• Graph-Based Physics-Guided Urban PM2.5 Air Quality Imputation with Constrained Monitoring Data
• Starting Positions Matter: A Study on Better Weight Initialization for Neural Network Quantization
• AI-Based Software Vulnerability Detection: A Systematic Literature Review
• Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning
• EnerBridge-DPO: Energy-Guided Protein Inverse Folding with Markov Bridges and Direct Preference Optimization
• FuncGNN: Learning Functional Semantics of Logic Circuits with Graph Neural Networks
• Benchmarking Quantum Architecture Search with Surrogate Assistance
• Positional Encoding meets Persistent Homology on Graphs
• Flow-Attentional Graph Neural Networks
• Graph Persistence goes Spectral
• Spectral Graph Neural Networks are Incomplete on Graphs with a Simple Spectrum
• Heterogeneous Sequel-Aware Graph Neural Networks for Sequential Learning
• Ignoring Directionality Leads to Compromised Graph Neural Network Explanations
• A Comprehensive Study on Medical Image Segmentation using Deep Neural Networks
• Multi-Granular Attention based Heterogeneous Hypergraph Neural Network
• Nature's Insight: A Novel Framework and Comprehensive Analysis of Agentic Reasoning Through the Lens of Neuroscience
• Forecasting UK Consumer Price Inflation with RaGNAR: Random Generalised Network Autoregressive Processes
• DiagNet: Detecting Objects using Diagonal Constraints on Adjacency Matrix of Graph Neural Network
• ExDiff: A Framework for Simulating Diffusion Processes on Complex Networks with Explainable AI Integration
• Clique detection using symmetry-restricted quantum circuits
• Principled Data Augmentation for Learning to Solve Quadratic Programming Problems
• Deep learning spinfoam vertex amplitudes: the Euclidean Barrett-Crane model
• On Universality Classes of Equivariant Networks
• Beyond Attention: Learning Spatio-Temporal Dynamics with Emergent Interpretable Topologies
• Dynamic Domain Adaptation-Driven Physics-Informed Graph Representation Learning for AC-OPF
• Autoregressive regularized score-based diffusion models for multi-scenarios fluid flow prediction
• GrapheonRL: A Graph Neural Network and Reinforcement Learning Framework for Constraint and Data-Aware Workflow Mapping and Scheduling in Heterogeneous HPC Systems
• A Benchmark Dataset for Graph Regression with Homogeneous and Multi-Relational Variants
• The Generalized Skew Spectrum of Graphs
• Parameter-Efficient Fine-Tuning with Attributed Patch Semantic Graph for Automated Patch Correctness Assessment
• Directed Homophily-Aware Graph Neural Network
• A Physics-Augmented GraphGPS Framework for the Reconstruction of 3D Riemann Problems from Sparse Data
• Multimodal Emotion Recognition in Conversations: A Survey of Methods, Trends, Challenges and Prospects
• Meta Pruning via Graph Metanetworks : A Universal Meta Learning Framework for Network Pruning
• TopoPoint: Enhance Topology Reasoning via Endpoint Detection in Autonomous Driving
• CoRe-GNN: Multilevel Message passing on Coarsened graphs
• Graph Style Transfer for Counterfactual Explainability
• Are GNNs Worth the Effort for IoT Botnet Detection? A Comparative Study of VAE-GNN vs. ViT-MLP and VAE-MLP Approaches
• Graph Attention Neural Network for Botnet Detection: Evaluating Autoencoder, VAE and PCA-Based Dimension Reduction
• Directed Semi-Simplicial Learning with Applications to Brain Activity Decoding
• McARL:Morphology-Control-Aware Reinforcement Learning for Generalizable Quadrupedal Locomotion
• A Game for Counting Logic Formula Size and an Application to Linear Orders
• Backward Oversmoothing: why is it hard to train deep Graph Neural Networks?
• Graph-Conditional Flow Matching for Relational Data Generation
• Oversmoothing, Oversquashing, Heterophily, Long-Range, and more: Demystifying Common Beliefs in Graph Machine Learning
• HOPSE: Scalable Higher-Order Positional and Structural Encoder for Combinatorial Representations
• A method for the systematic generation of graph XAI benchmarks via Weisfeiler-Leman coloring
• Differentiable Lifting for Topological Neural Networks
• LD-Scene: LLM-Guided Diffusion for Controllable Generation of Adversarial Safety-Critical Driving Scenarios
• Covariance Density Neural Networks
• Halting Recurrent GNNs and the Graded μ-Calculus
• A Set-Sequence Model for Time Series
• Graph Representational Learning: When Does More Expressivity Hurt Generalization?
• GNN-Suite: a Graph Neural Network Benchmarking Framework for Biomedical Informatics
• MSCI: Addressing CLIP's Inherent Limitations for Compositional Zero-Shot Learning
• Learning Repetition-Invariant Representations for Polymer Informatics
• SAR-GTR: Attributed Scattering Information Guided SAR Graph Transformer Recognition Algorithm
• Wireless Link Scheduling with State-Augmented Graph Neural Networks
• HYGMA: Hypergraph Coordination Networks with Dynamic Grouping for Multi-Agent Reinforcement Learning
• Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions
• Graph neural network-based structural classification of glass-forming liquids and its interpretation via self-attention mechanism
• Identifying Root Cause of bugs by Capturing Changed Code Lines with Relational Graph Neural Networks
• Safety-Critical Traffic Simulation with Guided Latent Diffusion Model
• Repetition Makes Perfect: Recurrent Graph Neural Networks Match Message-Passing Limit
• GNN For Muon Particle Momentum estimation
• Unifying approach to uniform expressivity of graph neural networks
• MatMMFuse: Multi-Modal Fusion model for Material Property Prediction
• FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs
• Di-BiLPS: Denoising induced Bidirectional Latent-PDE-Solver under Sparse Observations
• Code evolution for link prediction in complex networks
• Gauge-Equivariant Graph Neural Networks for Lattice Gauge Theories
• Concept Graph Convolutions: Message Passing in the Concept Space
• Disentangling multispecific antibody function with graph neural networks
• Combating Knowledge Corruption in Agent Systems: A Byzantine-Tolerant Secure Collaborative RAG Framework
• Spatiotemporal Graph Transformer for Traffic Intelligence in Edge Computing
• Systematic Literature Review on Vehicular Collaborative Perception -- A Computer Vision Perspective
• Efficient Document Retrieval with G-Retriever
• LBM-GNN: Graph Neural Network Enhanced Lattice Boltzmann Method
• MEGA: Second-Order Gradient Alignment for Catastrophic Forgetting Mitigation in GFSCIL
• EG-Gaussian: Epipolar Geometry and Graph Network Enhanced 3D Gaussian Splatting
• Denoising and Reconstruction of Nonlinear Dynamics using Truncated Reservoir Computing
• Inference-friendly Graph Compression for Graph Neural Networks
• Federated Spectral Graph Transformers Meet Neural Ordinary Differential Equations for Non-IID Graphs
• TacoDepth: Towards Efficient Radar-Camera Depth Estimation with One-stage Fusion
• The Impact of Dimensionality on the Stability of Node Embeddings
• Trajectory Encoding Temporal Graph Networks
• Visual Re-Ranking with Non-Visual Side Information
• Pseudo-Label Guided Real-World Image De-weathering: A Learning Framework with Imperfect Supervision
• xLSTM-ECG: Multi-label ECG Classification via Feature Fusion with xLSTM
• Spatially Directional Dual-Attention GAT for Spatial Fluoride Health Risk Modeling
• Graph Learning-Driven Multi-Vessel Association: Fusing Multimodal Data for Maritime Intelligence
• STF-GCN: A Multi-Domain Graph Convolution Network Method for Automatic Modulation Recognition via Adaptive Correlation
• Hypergraph Vision Transformers: Images are More than Nodes, More than Edges
• LeF‐MTP: Prioritizing GNN Test Cases by Fusing Model Uncertainty and Feature‐Space Confusability
• Boosting Relational Deep Learning with Pretrained Tabular Models