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KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support

Jun 16, 2021
Pierre Glaser, Michael Arbel, Arthur Gretton

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Annealed Flow Transport Monte Carlo

Feb 15, 2021
Michael Arbel, Alexander G. D. G. Matthews, Arnaud Doucet

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Deep Reinforcement Learning with Dynamic Optimism

Feb 09, 2021
Ted Moskovitz, Jack Parker-Holder, Aldo Pacchiano, Michael Arbel

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The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods

Jan 19, 2021
Louis Thiry, Michael Arbel, Eugene Belilovsky, Edouard Oyallon

* International Conference on Learning Representation (ICLR 2021), 2021, Vienna (online), Austria 

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Efficient Wasserstein Natural Gradients for Reinforcement Learning

Oct 12, 2020
Ted Moskovitz, Michael Arbel, Ferenc Huszar, Arthur Gretton

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Estimating Barycenters of Measures in High Dimensions

Jul 14, 2020
Samuel Cohen, Michael Arbel, Marc Peter Deisenroth

* In submission 

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A Non-Asymptotic Analysis for Stein Variational Gradient Descent

Jun 17, 2020
Anna Korba, Adil Salim, Michael Arbel, Giulia Luise, Arthur Gretton

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Synchronizing Probability Measures on Rotations via Optimal Transport

Apr 01, 2020
Tolga Birdal, Michael Arbel, Umut ┼×im┼čekli, Leonidas Guibas

* Accepted for publication at CVPR 2020, includes supplementary material. Project website: 

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KALE: When Energy-Based Learning Meets Adversarial Training

Mar 10, 2020
Michael Arbel, Liang Zhou, Arthur Gretton

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Kernelized Wasserstein Natural Gradient

Oct 25, 2019
Michael Arbel, Arthur Gretton, Wuchen Li, Guido Montufar

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Maximum Mean Discrepancy Gradient Flow

Jun 11, 2019
Michael Arbel, Anna Korba, Adil Salim, Arthur Gretton

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On gradient regularizers for MMD GANs

Oct 27, 2018
Michael Arbel, Dougal J. Sutherland, Mikołaj Bińkowski, Arthur Gretton

* Code available at . v2: NIPS camera-ready version 

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Kernel Conditional Exponential Family

Apr 08, 2018
Michael Arbel, Arthur Gretton

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Demystifying MMD GANs

Mar 21, 2018
Mikołaj Bińkowski, Dougal J. Sutherland, Michael Arbel, Arthur Gretton

* Published at ICLR 2018: . v4: actually-final version: non-existence of unbiased estimators for IPMs and FID; clarity edits to the main proof 

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Efficient and principled score estimation with Nystr├Âm kernel exponential families

Mar 13, 2018
Dougal J. Sutherland, Heiko Strathmann, Michael Arbel, Arthur Gretton

* v5: Final version to be published at AISTATS 2018 

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