Arthur Gretton
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
73
Venues
15
Active years
2003–2025
Best venue rank
A*
Where they publish
Papers
73 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ACL | Sleepless Nights, Sugary Days: Creating Synthetic Users with Health Conditions for Realistic Coaching Agent Interactions. | Taedong Yun, Eric Yang, Mustafa Safdari, Jong Ha Lee, Vaishnavi Vinod Kumar, S. Sara Mahdavi, Jonathan Amar, Derek Peyton, Reut Aharony, Andreas Michaelides, Logan Douglas Schneider, Isaac R. Galatzer-Levy, Yugang Jia, John Canny, Arthur Gretton, Maja J. Mataric |
| 2025 | AISTATS | Density Ratio-based Proxy Causal Learning Without Density Ratios. | Bariscan Bozkurt, Ben Deaner, Dimitri Meunier, Liyuan Xu, Arthur Gretton |
| 2025 | AISTATS | Credal Two-Sample Tests of Epistemic Uncertainty. | Siu Lun Chau, Antonin Schrab, Arthur Gretton, Dino Sejdinovic, Krikamol Muandet |
| 2025 | AISTATS | Spectral Representation for Causal Estimation with Hidden Confounders. | Haotian Sun, Antoine Moulin, Tongzheng Ren, Arthur Gretton, Bo Dai |
| 2025 | AISTATS | Kernel Single Proxy Control for Deterministic Confounding. | Liyuan Xu, Arthur Gretton |
| 2025 | ICLR | Deep MMD Gradient Flow without adversarial training. | Alexandre Galashov, Valentin De Bortoli, Arthur Gretton |
| 2025 | ICLR | Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression. | Juno Kim, Dimitri Meunier, Arthur Gretton, Taiji Suzuki, Zhu Li |
| 2025 | ICML | Learning-Order Autoregressive Models with Application to Molecular Graph Generation. | Zhe Wang, Jiaxin Shi, Nicolas Heess, Arthur Gretton, Michalis K. Titsias |
| 2025 | ICML | Accelerated Diffusion Models via Speculative Sampling. | Valentin De Bortoli, Alexandre Galashov, Arthur Gretton, Arnaud Doucet |
| 2025 | ICML | Distributional Diffusion Models with Scoring Rules. | Valentin De Bortoli, Alexandre Galashov, J. Swaroop Guntupalli, Guangyao Zhou, Kevin Patrick Murphy, Arthur Gretton, Arnaud Doucet |
| 2025 | UAI | A Unified Data Representation Learning for Non-parametric Two-sample Testing. | Xunye Tian, Liuhua Peng, Zhijian Zhou, Mingming Gong, Arthur Gretton, Feng Liu |
| 2024 | AISTATS | Proxy Methods for Domain Adaptation. | Katherine Tsai, Stephen R. Pfohl, Olawale Salaudeen, Nicole Chiou, Matt J. Kusner, Alexander D'Amour, Sanmi Koyejo, Arthur Gretton |
| 2024 | ICML | Distributional Bellman Operators over Mean Embeddings. | Li Kevin Wenliang, Grgoire Deltang, Matthew Aitchison, Marcus Hutter, Anian Ruoss, Arthur Gretton, Mark Rowland |
| 2024 | ICML | A Distributional Analogue to the Successor Representation. | Harley Wiltzer, Jesse Farebrother, Arthur Gretton, Yunhao Tang, Andr Barreto, Will Dabney, Marc G. Bellemare, Mark Rowland |
| 2024 | UAI | Conditional Bayesian Quadrature. | Zonghao Chen, Masha Naslidnyk, Arthur Gretton, Franois-Xavier Briol |
| 2023 | AISTATS | Adapting to Latent Subgroup Shifts via Concepts and Proxies. | Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D'Amour, Arthur Gretton, Sanmi Koyejo, Matt J. Kusner, Stephen R. Pfohl, Olawale Salaudeen, Jessica Schrouff, Katherine Tsai |
| 2023 | ICLR | Efficient Conditionally Invariant Representation Learning. | Roman Pogodin, Namrata Deka, Yazhe Li, Danica J. Sutherland, Victor Veitch, Arthur Gretton |
| 2023 | ICLR | A Neural Mean Embedding Approach for Back-door and Front-door Adjustment. | Liyuan Xu, Arthur Gretton |
| 2023 | ICML | A Kernel Stein Test of Goodness of Fit for Sequential Models. | Jerome Baum, Heishiro Kanagawa, Arthur Gretton |
| 2023 | UAI | Fast and scalable score-based kernel calibration tests. | Pierre Glaser, David Widmann, Fredrik Lindsten, Arthur Gretton |
| 2022 | AISTATS | Deep Layer-wise Networks Have Closed-Form Weights. | Chieh Tzu Wu, Aria Masoomi, Arthur Gretton, Jennifer G. Dy |
| 2022 | ICML | Importance Weighted Kernel Bayes' Rule. | Liyuan Xu, Yutian Chen, Arnaud Doucet, Arthur Gretton |
| 2022 | UAI | Causal inference with treatment measurement error: a nonparametric instrumental variable approach. | Yuchen Zhu, Limor Gultchin, Arthur Gretton, Matt J. Kusner, Ricardo Silva |
| 2021 | ICLR | Generalized Energy Based Models. | Michael Arbel, Liang Zhou, Arthur Gretton |
| 2021 | ICLR | Efficient Wasserstein Natural Gradients for Reinforcement Learning. | Ted Moskovitz, Michael Arbel, Ferenc Huszar, Arthur Gretton |
| 2021 | ICLR | Learning Deep Features in Instrumental Variable Regression. | Liyuan Xu, Yutian Chen, Siddarth Srinivasan, Nando de Freitas, Arnaud Doucet, Arthur Gretton |
| 2021 | ICML | Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction. | Afsaneh Mastouri, Yuchen Zhu, Limor Gultchin, Anna Korba, Ricardo Silva, Matt J. Kusner, Arthur Gretton, Krikamol Muandet |
| 2021 | UAI | A weaker faithfulness assumption based on triple interactions. | Alexander Marx, Arthur Gretton, Joris M. Mooij |
| 2020 | ICLR | Kernelized Wasserstein Natural Gradient. | Michael Arbel, Arthur Gretton, Wuchen Li, Guido Montfar |
| 2020 | ICML | Kernelized Stein Discrepancy Tests of Goodness-of-fit for Time-to-Event Data. | Tamara Fernandez, Nicolas Rivera, Wenkai Xu, Arthur Gretton |
| 2020 | ICML | Learning Deep Kernels for Non-Parametric Two-Sample Tests. | Feng Liu, Wenkai Xu, Jie Lu, Guangquan Zhang, Arthur Gretton, Danica J. Sutherland |
| 2019 | AISTATS | Kernel Exponential Family Estimation via Doubly Dual Embedding. | Bo Dai, Hanjun Dai, Arthur Gretton, Le Song, Dale Schuurmans, Niao He |
| 2019 | AISTATS | A maximum-mean-discrepancy goodness-of-fit test for censored data. | Tamara Fernandez, Arthur Gretton |
| 2019 | ESANN | Conditional BRUNO: a neural process for exchangeable labelled data. | Iryna Korshunova, Yarin Gal, Arthur Gretton, Joni Dambre |
| 2019 | ICML | Learning deep kernels for exponential family densities. | Wenliang Li, Danica J. Sutherland, Heiko Strathmann, Arthur Gretton |
| 2018 | AISTATS | Kernel Conditional Exponential Family. | Michael Arbel, Arthur Gretton |
| 2018 | AISTATS | Efficient and principled score estimation with Nystrm kernel exponential families. | Danica J. Sutherland, Heiko Strathmann, Michael Arbel, Arthur Gretton |
| 2018 | ICLR | Demystifying MMD GANs. | Mikolaj Binkowski, Danica J. Sutherland, Michael Arbel, Arthur Gretton |
| 2017 | ICLR | Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy. | Danica J. Sutherland, Hsiao-Yu Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alexander J. Smola, Arthur Gretton |
| 2017 | ICML | An Adaptive Test of Independence with Analytic Kernel Embeddings. | Wittawat Jitkrittum, Zoltn Szab, Arthur Gretton |
| 2016 | ICML | A Kernel Test of Goodness of Fit. | Kacper Chwialkowski, Heiko Strathmann, Arthur Gretton |
| 2016 | UAI | A Kernel Test for Three-Variable Interactions with Random Processes. | Paul K. Rubenstein, Kacper Chwialkowski, Arthur Gretton |
| 2015 | AISTATS | Two-stage sampled learning theory on distributions. | Zoltn Szab, Arthur Gretton, Barnabs Pczos, Bharath K. Sriperumbudur |
| 2015 | ICML | A low variance consistent test of relative dependency. | Wacha Bounliphone, Arthur Gretton, Arthur Tenenhaus, Matthew B. Blaschko |
| 2015 | UAI | Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages. | Wittawat Jitkrittum, Arthur Gretton, Nicolas Heess, S. M. Ali Eslami, Balaji Lakshminarayanan, Dino Sejdinovic, Zoltn Szab |
| 2014 | AAAI | Monte Carlo Filtering Using Kernel Embedding of Distributions. | Motonobu Kanagawa, Yu Nishiyama, Arthur Gretton, Kenji Fukumizu |
| 2014 | ICML | A Kernel Independence Test for Random Processes. | Kacper Chwialkowski, Arthur Gretton |
| 2014 | ICML | Kernel Mean Estimation and Stein Effect. | Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, Bernhard Schlkopf |
| 2014 | ICML | Kernel Adaptive Metropolis-Hastings. | Dino Sejdinovic, Heiko Strathmann, Maria Lomeli Garcia, Christophe Andrieu, Arthur Gretton |
| 2013 | ICML | Smooth Operators. | Steffen Grnewlder, Arthur Gretton, John Shawe-Taylor |
| 2013 | UAI | Hilbert Space Embeddings of Predictive State Representations. | Byron Boots, Geoffrey J. Gordon, Arthur Gretton |
| 2012 | ICML | Modelling transition dynamics in MDPs with RKHS embeddings. | Steffen Grnewlder, Guy Lever, Luca Baldassarre, Massimiliano Pontil, Arthur Gretton |
| 2012 | ICML | Conditional mean embeddings as regressors. | Steffen Grnewlder, Guy Lever, Arthur Gretton, Luca Baldassarre, Sam Patterson, Massimiliano Pontil |
| 2012 | ICML | Hypothesis testing using pairwise distances and associated kernels. | Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu |
| 2012 | UAI | Hilbert Space Embeddings of POMDPs. | Yu Nishiyama, Abdeslam Boularias, Arthur Gretton, Kenji Fukumizu |
| 2010 | ISIT | Non-parametric estimation of integral probability metrics. | Bharath K. Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schlkopf, Gert R. G. Lanckriet |
| 2009 | ICML | Detecting the direction of causal time series. | Jonas Peters, Dominik Janzing, Arthur Gretton, Bernhard Schlkopf |
| 2009 | KI | Generalized Clustering via Kernel Embeddings. | Stefanie Jegelka, Arthur Gretton, Bernhard Schlkopf, Bharath K. Sriperumbudur, Ulrike von Luxburg |
| 2009 | SDM | Near-optimal Supervised Feature Selection among Frequent Subgraphs. | Marisa Thoma, Hong Cheng, Arthur Gretton, Jiawei Han, Hans-Peter Kriegel, Alexander J. Smola, Le Song, Philip S. Yu, Xifeng Yan, Karsten M. Borgwardt |
| 2008 | ALT | Nonparametric Independence Tests: Space Partitioning and Kernel Approaches. | Arthur Gretton, Lszl Gyrfi |
| 2008 | COLT | Injective Hilbert Space Embeddings of Probability Measures. | Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert R. G. Lanckriet, Bernhard Schlkopf |
| 2008 | ICML | Tailoring density estimation via reproducing kernel moment matching. | Le Song, Xinhua Zhang, Alexander J. Smola, Arthur Gretton, Bernhard Schlkopf |
| 2007 | AAAI | A Kernel Approach to Comparing Distributions. | Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schlkopf, Alexander J. Smola |
| 2007 | ALT | A Hilbert Space Embedding for Distributions. | Alexander J. Smola, Arthur Gretton, Le Song, Bernhard Schlkopf |
| 2007 | DIS | A Hilbert Space Embedding for Distributions. | Alexander J. Smola, Arthur Gretton, Le Song, Bernhard Schlkopf |
| 2007 | ICML | A dependence maximization view of clustering. | Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt |
| 2007 | ICML | Supervised feature selection via dependence estimation. | Le Song, Alexander J. Smola, Arthur Gretton, Karsten M. Borgwardt, Justin Bedo |
| 2007 | ISMB | Gene selection via the BAHSIC family of algorithms. | Le Song, Justin Bedo, Karsten M. Borgwardt, Arthur Gretton, Alexander J. Smola |
| 2006 | ISMB | Integrating structured biological data by Kernel Maximum Mean Discrepancy. | Karsten M. Borgwardt, Arthur Gretton, Malte J. Rasch, Hans-Peter Kriegel, Bernhard Schlkopf, Alexander J. Smola |
| 2005 | AISTATS | Kernel Constrained Covariance for Dependence Measurement. | Arthur Gretton, Alexander J. Smola, Olivier Bousquet, Ralf Herbrich, Andrei Belitski, Mark Augath, Yusuke Murayama, Jon Pauls, Bernhard Schlkopf, Nikos K. Logothetis |
| 2005 | ALT | Measuring Statistical Dependence with Hilbert-Schmidt Norms. | Arthur Gretton, Olivier Bousquet, Alexander J. Smola, Bernhard Schlkopf |
| 2003 | ICASSP | On-line one-class support vector machines. An application to signal segmentation. | Arthur Gretton, Frdric Desobry |
| 2003 | ICASSP | The kernel mutual information. | Arthur Gretton, Ralf Herbrich, Alexander J. Smola |