Kaski, Samuel
- Likelihood-free inference by ratio estimation
2016/11/30 by Thomas, Owen, Dutta, Ritabrata, Corander, Jukka +2 · 13 citations
#Computation (stat.CO) #FOS: Computer and information sciences #Machine Learning (stat.ML) #Methodology (stat.ME)
- Prior knowledge elicitation: The past, present, and future
2021/12/01 by Petrus Mikkola, Osvaldo A. Martin, Mikkola, Petrus +21 · 11 citations
Computer Science · Mathematics · Decision Sciences · #Bayesian Modeling and Causal Inference #Statistical Methods and Bayesian Inference #Forecasting Techniques and Applications
- Rethinking pooling in graph neural networks
2020/10/22 by Diego Mesquita, Mesquita, Diego, Amauri H. Souza +3 · 8 citations
Computer Science · #Advanced Graph Neural Networks #Graph Theory and Algorithms #Multimodal Machine Learning Applications
- Group Factor Analysis
2014/11/21 by Arto Klami, Seppo Virtanen, Klami, Arto +5 · 5 citations
Biochemistry, Genetics and Molecular Biology · #Gene expression and cancer classification #Bioinformatics and Genomic Networks #Gene Regulatory Network Analysis
- Learning Robust Statistics for Simulation-based Inference under Model Misspecification
2023/05/25 by Daolang Huang, Ayush Bharti, Huang, Daolang +7 · 13 citations
Computer Science · Mathematics · #Computation (stat.CO) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Markov Chains and Monte Carlo Methods
- Provably expressive temporal graph networks
2022/09/29 by Souza, Amauri H., Mesquita, Diego, Kaski, Samuel +1 · 9 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG)
- Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo
2015/08/18 by Markus Heinonen, Henrik Mannerström, Heinonen, Markus +7 · 4 citations
Computer Science · Mathematics · #Gaussian Processes and Bayesian Inference #Advanced Multi-Objective Optimization Algorithms #Markov Chains and Monte Carlo Methods
- Machine Teaching of Active Sequential Learners
2018/09/08 by Tomi Peltola, Mustafa Mert Çelikok, Peltola, Tomi +5 · 1 voice · 2 citations
Computer Science · Decision Sciences · Mathematics · #Advanced Bandit Algorithms Research #Artificial Intelligence (cs.AI) #Data Stream Mining Techniques #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #cs.AI #cs.HC #cs.LG #stat.ML
- Differentially Private Bayesian Learning on Distributed Data
2017/03/03 by Mikko Heikkilä, Heikkilä, Mikko, Eemil Lagerspetz +9 · 6 citations
Computer Science · Decision Sciences · #Privacy-Preserving Technologies in Data #Distributed Sensor Networks and Detection Algorithms #Data Quality and Management
- TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series
2023/05/19 by Alexander Nikitin, Nikitin, Alexander, Letizia Iannucci +3 · 6 citations
Computer Science · #Data Visualization and Analytics #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Music and Audio Processing #Time Series Analysis and Forecasting
- Amortized Bayesian Experimental Design for Decision-Making
2024/11/04 by Daolang Huang, Huang, Daolang, Yujia Guo +5 · 2 voices · 6 citations
Decision Sciences · #Optimal Experimental Design Methods
- Amortized Probabilistic Conditioning for Optimization, Simulation and Inference
2024/10/20 by Paul E. Chang, Nasrulloh Loka, Chang, Paul E. +9 · 1 voice · 9 citations
Computer Science · Engineering · Mathematics · #Embedded Systems Design Techniques #Manufacturing Process and Optimization #Parallel Computing and Optimization Techniques #cs.LG #stat.ML
- Video-Language Critic: Transferable Reward Functions for Language-Conditioned Robotics
2024/05/30 by Minttu Alakuijala, Alakuijala, Minttu, Reginald McLean +11 · 6 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimodal Machine Learning Applications #Robotics (cs.RO)
- Deconfounded Representation Similarity for Comparison of Neural Networks
2022/01/31 by Tianyu Cui, Yogesh Kumar, Cui, Tianyu +5 · 3 citations
Computer Science · Materials Science · #Domain Adaptation and Few-Shot Learning #Topic Modeling #Machine Learning in Materials Science
- Approximate Bayesian Computation with Domain Expert in the Loop
2022/01/28 by Ayush Bharti, Bharti, Ayush, Louis Filstroff +3 · 3 citations
Computer Science · Mathematics · #Algorithms and Data Compression #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Markov Chains and Monte Carlo Methods
- Multi-Fidelity Bayesian Optimization with Unreliable Information Sources
2022/10/25 by Mikkola, Petrus, Martinelli, Julien, Filstroff, Louis +1 · 3 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- DroneDiffusion: Robust Quadrotor Dynamics Learning with Diffusion Models
2024/09/17 by Das, Avirup, Yadav, Rishabh Dev, Sun, Sihao +3 · 7 citations
#FOS: Computer and information sciences #Robotics (cs.RO)
- Federated Stochastic Gradient Langevin Dynamics
2020/04/23 by Khaoula El Mekkaoui, Mekkaoui, Khaoula El, Diego Mesquita +5 · 2 citations
Computer Science · Mathematics · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Stochastic Gradient Optimization Techniques
- Variational multiple shooting for Bayesian ODEs with Gaussian processes
2021/06/21 by Hegde, Pashupati, Yıldız, Çağatay, Lähdesmäki, Harri +2 · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Compositional Sculpting of Iterative Generative Processes
2023/09/28 by Garipov, Timur, De Peuter, Sebastiaan, Yang, Ge +3 · 3 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG)
- Optimally-Weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference
2023/01/27 by Ayush Bharti, Bharti, Ayush, Masha Naslidnyk +7 · 4 citations
Computer Science · Decision Sciences · Mathematics · #Advanced Statistical Process Monitoring #Computation (stat.CO) #FOS: Computer and information sciences #Machine Learning (stat.ML) #Machine Learning and Algorithms #Methodology (stat.ME) #Statistical Methods and Bayesian Inference
- Tackling covariate shift with node-based Bayesian neural networks
2022/06/06 by Trung Trinh, Trinh, Trung, Markus Heinonen +5 · 2 citations
Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Machine Learning and Data Classification
- Targeted Active Learning for Bayesian Decision-Making
2021/06/08 by Louis Filstroff, Filstroff, Louis, Iiris Sundin +9 · 2 citations
Computer Science · Decision Sciences · #Advanced Statistical Process Monitoring #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
- Kernelized Bayesian Matrix Factorization
2012/11/06 by Gönen, Mehmet, Khan, Suleiman A., Kaski, Samuel · 1 citation
#FOS: Computer and information sciences #Machine Learning (stat.ML)
- Variational zero-inflated Gaussian processes with sparse kernels
2018/03/13 by Pashupati Hegde, Markus Heinonen, Hegde, Pashupati +3 · 1 citation
Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Statistical Mechanics and Entropy #Target Tracking and Data Fusion in Sensor Networks
- Active Learning for Decision-Making from Imbalanced Observational Data
2019/04/10 by Iiris Sundin, Sundin, Iiris, Peter Schulam +9 · 1 citation
Computer Science · Mathematics · #Advanced Causal Inference Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Statistical Methods in Clinical Trials
- Interactive AI with a Theory of Mind
2019/12/01 by Çelikok, Mustafa Mert, Peltola, Tomi, Daee, Pedram +1 · 1 citation
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC)
- Misspecification-robust likelihood-free inference in high dimensions
2020/02/21 by Owen Thomas, Thomas, Owen, Raquel Sá‐Leão +9 · 1 citation
Computer Science · #Bayesian Methods and Mixture Models #Computation (stat.CO) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Machine Learning and Algorithms #Methodology (stat.ME)
- Differentially private cross-silo federated learning
2020/07/10 by Heikkilä, Mikko A., Koskela, Antti, Shimizu, Kana +2 · 1 citation
#Cryptography and Security (cs.CR) #Distributed #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Parallel #and Cluster Computing (cs.DC)
- Practical Equivariances via Relational Conditional Neural Processes
2023/06/19 by Daolang Huang, Manuel Haußmann, Huang, Daolang +13 · 2 citations
Computer Science · #Neural Networks and Applications #Explainable Artificial Intelligence (XAI) #Adversarial Robustness in Machine Learning
- ABC of the Future
2021/12/23 by Henri Pesonen, Umberto Simola, Pesonen, Henri +19 · 1 citation
Computer Science · Mathematics · #Applications (stat.AP) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Markov Chains and Monte Carlo Methods #Methodology (stat.ME) #Statistical Methods and Bayesian Inference
- Non-separable Spatio-temporal Graph Kernels via SPDEs
2021/11/16 by Alexander Nikitin, St. John, Nikitin, Alexander +5 · 1 citation
Computer Science · Environmental Science · #Gaussian Processes and Bayesian Inference #Time Series Analysis and Forecasting #Air Quality Monitoring and Forecasting
- Noise-Aware Statistical Inference with Differentially Private Synthetic Data
2022/05/28 by Ossi Räisä, Räisä, Ossi, Joonas Jälkö +5 · 1 citation
Computer Science · Engineering · Decision Sciences · #Privacy-Preserving Technologies in Data #Traffic Prediction and Management Techniques #Data Quality and Management
- Bayesian Optimization Augmented with Actively Elicited Expert Knowledge
2022/08/18 by Daolang Huang, Louis Filstroff, Huang, Daolang +7 · 1 citation
Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and Data Classification
- PinView: Implicit Feedback in Content-Based Image Retrieval
2014/10/02 by Zakria Hussain, Hussain, Zakria, Arto Klami +15 · 1 citation
Computer Science · #Image Retrieval and Classification Techniques #Advanced Image and Video Retrieval Techniques #Video Analysis and Summarization
- Likelihood-free inference via classification
2014/07/18 by Michael U. Gutmann, Gutmann, Michael U., Ritabrata Dutta +5 · 1 citation
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Computation (stat.CO) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Methodology (stat.ME)
- Memento No More: Coaching AI Agents to Master Multiple Tasks via Hints Internalization
2025/02/03 by Minttu Alakuijala, Ya Gao, Alakuijala, Minttu +11 · 3 citations
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Reinforcement Learning in Robotics
- Online simulator-based experimental design for cognitive model selection
2023/03/03 by Alexander Aushev, Aini Putkonen, Aushev, Alexander +11 · 1 citation
Computer Science · #Data Stream Mining Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and Data Classification
- Expert-aided causal discovery of ancestral graphs
2023/09/21 by Tiago da Silva, da Silva, Tiago, Bruna Bazaluk +15 · 1 voice · 1 citation
Computer Science · #Advanced Graph Neural Networks #Bayesian Modeling and Causal Inference #Graph Theory and Algorithms
- In-n-Out: Calibrating Graph Neural Networks for Link Prediction
2024/03/07 by Erik Jhones Freitas do Nascimento, Nascimento, Erik, Diego Mesquita +5 · 1 citation
Computer Science · #Advanced Graph Neural Networks #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Software Testing and Debugging Techniques
- From Alexnet to Transformers: Measuring the Non-linearity of Deep Neural Networks with Affine Optimal Transport
2023/10/17 by Bouniot, Quentin, Redko, Ievgen, Mallasto, Anton +6 · 1 citation
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Improving robustness to corruptions with multiplicative weight perturbations
2024/06/24 by Trung Trinh, Trinh, Trung, Markus Heinonen +5 · 1 citation
Social Sciences · #Corruption and Economic Development
- Open Ad Hoc Teamwork with Cooperative Game Theory
2024/02/23 by Jianhong Wang, Yang Li, Wang, Jianhong +7 · 2 citations
Computer Science · #Distributed systems and fault tolerance #FOS: Computer and information sciences #Machine Learning (cs.LG) #Mobile Crowdsensing and Crowdsourcing #Multi-Agent Systems and Negotiation #Multiagent Systems (cs.MA)
- Input-gradient space particle inference for neural network ensembles
2023/06/05 by Trung Trinh, Markus Heinonen, Trinh, Trung +5 · 1 citation
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications
- PABBO: Preferential Amortized Black-Box Optimization
2025/03/02 by Xinyu Zhang, Daolang Huang, Zhang, Xinyu +5 · 3 citations
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Stochastic Gradient Optimization Techniques
- ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition
2025/06/08 by Daolang Huang, Huang, Daolang, Wen, Xinyi +6 · 2 citations
Computer Science · #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
- Cost-aware simulation-based inference
2024/10/10 by Ayush Bharti, Bharti, Ayush, Daolang Huang +6 · 1 voice · 1 citation
Decision Sciences · #Simulation Techniques and Applications #cs.LG #stat.CO #stat.ML
- Learning spectrograms with convolutional spectral kernels
2019/05/23 by Zheyang Shen, Markus Heinonen, Shen, Zheyang +3 · 1 citation
Computer Science · Engineering · #Control Systems and Identification #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications
- Bayesian Active Learning in the Presence of Nuisance Parameters
2023/10/23 by Sabina J. Sloman, Ayush Bharti, Sloman, Sabina J. +3 · 1 citation
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification