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Michael Arbel
Michael Arbel
Inria - Univ. Grenoble Alpes
Bestätigte E-Mail-Adresse bei inria.fr - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Demystifying mmd gans
M Bińkowski, DJ Sutherland, M Arbel, A Gretton
International Conference on Learning Representations (ICLR) 2018, 2018
5842018
On gradient regularizers for MMD GANs
M Arbel, DJ Sutherland, M Bińkowski, A Gretton
Advances in Neural Information Processing Systems (NeurIPS) 2018, 2018
822018
Maximum mean discrepancy gradient flow
M Arbel, A Korba, A Salim, A Gretton
Advances in Neural Information Processing Systems (NeurIPS) 2019, 2019
572019
Generalized Energy Based Models
M Arbel, L Zhou, A Gretton
International Conference on Learning Representations (ICLR) 2021, 2021
52*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 (AISTATS …, 2018
312018
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
282020
Kernel conditional exponential family
M Arbel, A Gretton
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2018
222018
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, 1569 …, 2020
202020
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
12*2021
Kernelized Wasserstein Natural Gradient
M Arbel, A Gretton, W Li, G Montúfar
International Conference on Learning Representations (ICLR) 2020, 2020
122020
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
82021
Estimating barycenters of measures in high dimensions
S Cohen, M Arbel, MP Deisenroth
arXiv preprint arXiv:2007.07105, 2020
72020
Annealed Flow Transport Monte Carlo
M Arbel, AGDG Matthews, A Doucet
International Conference on Machine Learning (ICML) 2021, 2021
62021
Amortized implicit differentiation for stochastic bilevel optimization
M Arbel, J Mairal
International Conference on Learning Representations (ICLR) 2022, 2021
42021
Efficient wasserstein natural gradients for reinforcement learning
T Moskovitz, M Arbel, F Huszar, A Gretton
International Conference on Learning Representations (ICLR) 2021, 2021
42021
Continual Repeated Annealed Flow Transport Monte Carlo
A Matthews, M Arbel, DJ Rezende, A Doucet
International Conference on Machine Learning, 15196-15219, 2022
22022
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 (AISTATS …, 2021
22021
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
Non-Convex Bilevel Games with Critical Point Selection Maps
M Arbel, J Mairal
arXiv preprint arXiv:2207.04888, 2022
2022
Methods for Optimization and Regularization of Generative Models
M Arbel
UCL (University College London), 2021
2021
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