Arthur Gretton
- Demystifying MMD GANs
2018/01/04 by Mikołaj Bińkowski, Danica J. Sutherland, Bińkowski, Mikołaj +5 · 127 citations
Computer Science · Physics and Astronomy · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
- A Kernel Method for the Two-Sample Problem
2008/05/15 by Arthur Gretton, Karsten Borgwardt, Gretton, Arthur +7 · 59 citations
Computer Science · #Data Stream Mining Techniques #Bayesian Modeling and Causal Inference #Machine Learning and Algorithms
- Hilbert space embeddings and metrics on probability measures
2009/07/30 by Bharath K. Sriperumbudur, Arthur Gretton, Sriperumbudur, Bharath K. +7 · 30 citations
Computer Science · Medicine · #Advanced Neuroimaging Techniques and Applications #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Statistics Theory (math.ST) #Topological and Geometric Data Analysis
- On integral probability metrics, ϕ-divergences and binary classification
2009/01/18 by Bharath K. Sriperumbudur, Sriperumbudur, Bharath K., Kenji Fukumizu +7 · 11 citations
Mathematics · Physics and Astronomy · #Advanced Statistical Methods and Models #FOS: Computer and information sciences #Fuzzy Systems and Optimization #Information Theory (cs.IT) #Statistical Mechanics and Entropy
- Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy
2016/11/14 by Danica J. Sutherland, Hsiao-Yu Fish Tung, Sutherland, Danica J. +11 · 12 citations
Computer Science · #Artificial Intelligence (cs.AI) #Bayesian Methods and Mixture Models #Digital Media Forensic Detection #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Neural and Evolutionary Computing (cs.NE)
- Maximum Mean Discrepancy Gradient Flow
2019/06/11 by Michael Arbel, Arbel, Michael, Anna Korba +5 · 12 citations
Computer Science · #Generative Adversarial Networks and Image Synthesis #Advanced Image Processing Techniques #Image and Signal Denoising Methods
- Conditional mean embeddings as regressors - supplementary
2012/05/21 by Steffen Grünewälder, Guy Lever, Grünewälder, Steffen +8 · 9 citations
Decision Sciences · Mathematics · #Advanced Statistical Methods and Models #Advanced Statistical Process Monitoring #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Inference
- Fast Two-Sample Testing with Analytic Representations of Probability\n Measures
2015/06/15 by Kacper Chwialkowski, Chwialkowski, Kacper, Aaditya Ramdas +5 · 10 citations
Computer Science · Decision Sciences · Mathematics · #62G10 #Advanced Bandit Algorithms Research #Algorithms and Data Compression #FOS: Computer and information sciences #G.3 #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Statistical Methods and Inference
- Accelerated Diffusion Models via Speculative Sampling
2025/01/09 by Valentin De Bortoli, De Bortoli, Valentin, Alexandre Galashov +5 · 4 voices · 8 citations
Mathematics · #Statistical Methods and Inference #cs.LG #stat.ML
- Kernel Instrumental Variable Regression
2019/06/01 by Rahul Singh, Maneesh Sahani, Singh, Rahul +3 · 8 citations
Computer Science · Engineering · Mathematics · #Distributed Sensor Networks and Detection Algorithms #Econometrics (econ.EM) #FOS: Computer and information sciences #FOS: Economics and business #FOS: Mathematics #Functional Analysis (math.FA) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference #Statistics Theory (math.ST)
- Stein's Method Meets Computational Statistics: A Review of Some Recent Developments
2021/05/07 by Andreas Anastasiou, Alessandro Barp, Anastasiou, Andreas +25 · 10 citations
Mathematics · #Random Matrices and Applications #Advanced Combinatorial Mathematics #Statistical Methods and Bayesian Inference
- Self-Supervised Learning with Kernel Dependence Maximization
2021/06/15 by Yazhe Li, Roman Pogodin, Li, Yazhe +5 · 8 citations
Computer Science · #Anomaly Detection Techniques and Applications #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- Density Estimation in Infinite Dimensional Exponential Families
2013/12/12 by Bharath K. Sriperumbudur, Sriperumbudur, Bharath, Kenji Fukumizu +7 · 7 citations
Mathematics · Computer Science · #Markov Chains and Monte Carlo Methods #Bayesian Methods and Mixture Models #Statistical Methods and Inference
- Modelling transition dynamics in MDPs with RKHS embeddings
2012/06/18 by Steffen Grünewälder, Guy Lever, Grunewalder, Steffen +7 · 7 citations
Computer Science · #Reinforcement Learning in Robotics #Gaussian Processes and Bayesian Inference #Machine Learning and Algorithms
- A Non-Asymptotic Analysis for Stein Variational Gradient Descent
2020/06/17 by Anna Korba, Adil Salim, Korba, Anna +7 · 6 citations
Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Point processes and geometric inequalities #Random Matrices and Applications
- Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment\n Restriction
2021/05/10 by Afsaneh Mastouri, Mastouri, Afsaneh, Yuchen Zhu +13 · 7 citations
Mathematics · #Advanced Causal Inference Techniques #Statistical Methods and Inference
- Learning Deep Features in Instrumental Variable Regression
2020/10/14 by Liyuan Xu, Xu, Liyuan, Yutian Chen +9 · 6 citations
Computer Science · Decision Sciences · Mathematics · #Advanced Bandit Algorithms Research #Advanced Causal Inference Techniques #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- A Wild Bootstrap for Degenerate Kernel Tests
2014/08/23 by Kacper Chwialkowski, Chwialkowski, Kacper, Dino Sejdinović +3 · 4 citations
Computer Science · Economics, Econometrics and Finance · Mathematics · #62G10 #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Financial Risk and Volatility Modeling #Machine Learning (stat.ML) #Statistical Methods and Inference
- Interpretable Distribution Features with Maximum Testing Power
2016/05/22 by Wittawat Jitkrittum, Jitkrittum, Wittawat, Zoltán Szabó +5 · 5 citations
Mathematics · Computer Science · #Statistical Methods and Inference #Image Retrieval and Classification Techniques #Bayesian Methods and Mixture Models
- Optimal Rates for Regularized Conditional Mean Embedding Learning
2022/08/02 by Zhu Li, Dimitri Meunier, Li, Zhu +5 · 6 citations
Mathematics · Computer Science · #Statistical Methods and Inference #Domain Adaptation and Few-Shot Learning #Distributed Sensor Networks and Detection Algorithms
- A Kernel Independence Test for Random Processes
2014/02/18 by Kacper Chwialkowski, Chwialkowski, Kacper, Arthur Gretton +1 · 3 citations
Computer Science · Economics, Econometrics and Finance · Mathematics · #62G10 #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Financial Risk and Volatility Modeling #Machine Learning (stat.ML) #Statistical Methods and Inference
- Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm
2023/12/12 by Zhu Li, Dimitri Meunier, Li, Zhu +5 · 7 citations
Decision Sciences · Engineering · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Mathematical Approximation and Integration #Probabilistic and Robust Engineering Design #Sparse and Compressive Sensing Techniques
- Distributional Diffusion Models with Scoring Rules
2025/02/04 by Valentin De Bortoli, De Bortoli, Valentin, Alexandre Galashov +12 · 3 voices · 6 citations
Social Sciences · #Insurance, Mortality, Demography, Risk Management #cs.LG #stat.ML
- Deep Proxy Causal Learning and its Application to Confounded Bandit\n Policy Evaluation
2021/06/07 by Liyuan Xu, Heishiro Kanagawa, Xu, Liyuan +3 · 4 citations
Decision Sciences · Economics, Econometrics and Finance · Mathematics · #Advanced Bandit Algorithms Research #Advanced Causal Inference Techniques #FOS: Computer and information sciences #Health Systems, Economic Evaluations, Quality of Life #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Kernel Mean Shrinkage Estimators
2014/05/21 by Krikamol Muandet, Bharath K. Sriperumbudur, Muandet, Krikamol +7 · 2 citations
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Statistical Methods and Inference #Gaussian Processes and Bayesian Inference
- Spectral Representation for Causal Estimation with Hidden Confounders
2024/07/15 by Haotian Sun, Antoine Moulin, Sun, Haotian +7 · 1 voice · 5 citations
Computer Science · Engineering · Mathematics · #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Fault Detection and Control Systems #Machine Learning (cs.LG) #Machine Learning (stat.ML) #cs.LG #stat.ML
- Practical Kernel Tests of Conditional Independence
2024/02/20 by Roman Pogodin, Antonin Schrab, Pogodin, Roman +7 · 5 citations
Mathematics · Computer Science · #Statistical Methods and Inference #Advanced Statistical Methods and Models #Bayesian Modeling and Causal Inference
- Foundations of Multivariate Distributional Reinforcement Learning
2024/08/31 by Harley Wiltzer, Wiltzer, Harley, Jesse Farebrother +5 · 2 voices · 3 citations
Agricultural and Biological Sciences · Computer Science · #Food Supply Chain Traceability #Statistical and Computational Modeling #cs.LG #math.OC #stat.ML
- B-tests: Low Variance Kernel Two-Sample Tests
2013/07/08 by Wojciech Zaremba, Zaremba, Wojciech, Arthur Gretton +3 · 2 citations
Computer Science · Decision Sciences · Mathematics · #Advanced Statistical Process Monitoring #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Inference
- Credal Two-Sample Tests of Epistemic Uncertainty
2024/10/16 by Siu Lun Chau, Chau, Siu Lun, Antonin Schrab +8 · 2 voices · 3 citations
Computer Science · Mathematics · #Bayesian Modeling and Causal Inference #Advanced Causal Inference Techniques #Adversarial Robustness in Machine Learning
- A Distributional Analogue to the Successor Representation
2024/02/13 by Harley Wiltzer, Jesse Farebrother, Wiltzer, Harley +13 · 3 citations
Economics, Econometrics and Finance · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Insurance and Financial Risk Management #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Adapting to Latent Subgroup Shifts via Concepts and Proxies
2022/12/21 by Ibrahim Alabdulmohsin, Alabdulmohsin, Ibrahim, Nicole Chiou +17 · 2 citations
Computer Science · #Domain Adaptation and Few-Shot Learning #Text and Document Classification Technologies
- Informative Features for Model Comparison
2018/10/27 by Wittawat Jitkrittum, Jitkrittum, Wittawat, Heishiro Kanagawa +9 · 2 citations
Computer Science · #46E22 #62G10 #Data Stream Mining Techniques #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #G.3 #I.2.6 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- Mind the Graph When Balancing Data for Fairness or Robustness
2024/06/25 by Jessica Schrouff, Alexis Bellot, Schrouff, Jessica +13 · 3 citations
Computer Science · #Bayesian Modeling and Causal Inference
- Model-based Kernel Sum Rule: Kernel Bayesian Inference with Probabilistic Models
2014/09/18 by Yu Nishiyama, Motonobu Kanagawa, Nishiyama, Yu +5 · 1 citation
Computer Science · #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Machine Learning and Algorithms #Methodology (stat.ME)
- A maximum-mean-discrepancy goodness-of-fit test for censored data
2018/10/09 by Tamara Fernández, Arthur Gretton, Fernández, Tamara +1 · 1 citation
Mathematics · #Statistical Methods and Inference #Statistical Methods and Bayesian Inference #Statistical Distribution Estimation and Applications
- BRUNO: A Deep Recurrent Model for Exchangeable Data
2018/02/21 by Iryna Korshunova, Korshunova, Iryna, Jonas Degrave +9 · 1 citation
Computer Science · #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Machine Learning in Healthcare
- Kernelized Stein Discrepancy Tests of Goodness-of-fit for Time-to-Event Data
2020/08/19 by Tamara Fernández, Nicolás Rivera, Fernandez, Tamara +5 · 2 citations
Mathematics · Engineering · #Statistical Distribution Estimation and Applications #Statistical Methods and Bayesian Inference #Reliability and Maintenance Optimization
- Deep MMD Gradient Flow without adversarial training
2024/05/10 by Alexandre Galashov, Galashov, Alexandre, Valentin De Bortoli +3 · 2 citations
Computer Science · Engineering · #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Fluid Dynamics and Turbulent Flows #Machine Learning (cs.LG) #Plasma and Flow Control in Aerodynamics
- KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint\n Support
2021/06/16 by Pierre Glaser, Michael Arbel, Glaser, Pierre +3 · 1 citation
Computer Science · Decision Sciences · #Gaussian Processes and Bayesian Inference #Probabilistic and Robust Engineering Design #Adversarial Robustness in Machine Learning
- Proxy Methods for Domain Adaptation
2024/03/12 by Katherine Tsai, Tsai, Katherine, Stephen Pfohl +13 · 1 citation
Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- Demystifying Spectral Feature Learning for Instrumental Variable Regression
2025/06/12 by Dimitri Meunier, Meunier, Dimitri, Antoine Moulin +7 · 3 citations
Computer Science · Mathematics · #Advanced Causal Inference Techniques #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Statistical Methods and Inference
- Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms
2024/05/23 by Dimitri Meunier, Zikai Shen, Meunier, Dimitri +7 · 1 citation
Computer Science · Engineering · #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Sparse and Compressive Sensing Techniques
- Density Ratio-based Proxy Causal Learning Without Density Ratios
2025/03/11 by Bariscan Bozkurt, Bozkurt, Bariscan, Ben Deaner +7 · 1 voice · 1 citation
Computer Science · Engineering · #Bayesian Modeling and Causal Inference #Fault Detection and Control Systems #cs.LG
- (De)-regularized Maximum Mean Discrepancy Gradient Flow
2024/09/23 by Zonghao Chen, Chen, Zonghao, Aratrika Mustafi +9 · 1 citation
Engineering · #Advanced Numerical Analysis Techniques
- Prompting Strategies for Enabling Large Language Models to Infer Causation from Correlation
2024/12/18 by Eleni Sgouritsa, Virginia Aglietti, Sgouritsa, Eleni +9 · 1 citation
Computer Science · #Natural Language Processing Techniques #Topic Modeling
- Aggregation of Statistical Evidence under Exchangeability
2026/07/17 by Antonin Schrab, Rajen Shah, Arthur Gretton +1
#stat.ME #cs.LG #math.ST #stat.ML #stat.TH