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Michael Arbel
Michael Arbel
Inria - Univ. Grenoble Alpes
Verified email at inria.fr - Homepage
Title
Cited by
Cited by
Year
Demystifying mmd gans
M Bińkowski, DJ Sutherland, M Arbel, A Gretton
International Conference on Learning Representations (ICLR) 2018, 2018
5532018
On gradient regularizers for MMD GANs
M Arbel, DJ Sutherland, M Bińkowski, A Gretton
Advances in Neural Information Processing Systems (NeurIPS) 2018, 2018
802018
Maximum mean discrepancy gradient flow
M Arbel, A Korba, A Salim, A Gretton
Advances in Neural Information Processing Systems (NeurIPS) 2019, 2019
542019
Generalized Energy Based Models
M Arbel, L Zhou, A Gretton
International Conference on Learning Representations (ICLR) 2021, 2021
47*2021
Efficient and principled score estimation with Nystr\" om kernel exponential families
DJ Sutherland, H Strathmann, M Arbel, A Gretton
International Conference on Artificial Intelligence and Statistics (AISTATSá…, 2018
29*2018
A non-asymptotic analysis for Stein variational gradient descent
A Korba, A Salim, M Arbel, G Luise, A Gretton
Advances in Neural Information Processing Systems (NeurIPS) 2020 33, 2020
272020
Kernel conditional exponential family
M Arbel, A Gretton
International Conference on Artificial Intelligence and Statistics (AISTATSá…, 2018
212018
Synchronizing probability measures on rotations via optimal transport
T Birdal, M Arbel, U Simsekli, LJ Guibas
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020, 1569á…, 2020
192020
Kernelized Wasserstein Natural Gradient
M Arbel, A Gretton, W Li, G Mont˙far
International Conference on Learning Representations (ICLR) 2020, 2020
122020
Tactical Optimism and Pessimism for Deep Reinforcement Learning
T Moskovitz, J Parker-Holder, A Pacchiano, M Arbel, MI Jordan
Advances in Neural Information Processing Systems (NeurIPS) 2021, 2021
10*2021
Estimating barycenters of measures in high dimensions
S Cohen, M Arbel, MP Deisenroth
arXiv preprint arXiv:2007.07105, 2020
72020
The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods
L Thiry, M Arbel, E Belilovsky, E Oyallon
International Conference on Learning Representations (ICLR) 2022, 2021
62021
Annealed Flow Transport Monte Carlo
M Arbel, AGDG Matthews, A Doucet
International Conference on Machine Learning (ICML) 2021, 2021
42021
Amortized implicit differentiation for stochastic bilevel optimization
M Arbel, J Mairal
International Conference on Learning Representations (ICLR) 2022, 2021
32021
Efficient wasserstein natural gradients for reinforcement learning
T Moskovitz, M Arbel, F Huszar, A Gretton
International Conference on Learning Representations (ICLR) 2021, 2021
32021
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support
P Glaser, M Arbel, A Gretton
Advances in Neural Information Processing Systems (NeurIPS) 2021, 2021
22021
Continual Repeated Annealed Flow Transport Monte Carlo
AGDG Matthews, M Arbel, DJ Rezende, A Doucet
arXiv preprint arXiv:2201.13117, 2022
12022
Towards an Understanding of Default Policies in Multitask Policy Optimization
T Moskovitz, M Arbel, J Parker-Holder, A Pacchiano
International Conference on Artificial Intelligence and Statistics (AISTATSá…, 2021
2021
Methods for Optimization and Regularization of Generative Models
M Arbel
UCL (University College London), 2021
2021
Synchronizing Probability Measures on Rotations via Optimal Transport Open Website
T Birdal, M Arbel, U Şimşekli, L Guibas
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