Michael Arbel
Michael Arbel
Gatsby Computational Neuroscience Unit, UCL
Email verificata su ucl.ac.uk - Home page
Titolo
Citata da
Citata da
Anno
Demystifying mmd gans
M Bińkowski, DJ Sutherland, M Arbel, A Gretton
International Conference on Learning Representations, 2018
3142018
On gradient regularizers for MMD GANs
M Arbel, DJ Sutherland, M Bińkowski, A Gretton
arXiv preprint arXiv:1805.11565, 2018
622018
Maximum mean discrepancy gradient flow
M Arbel, A Korba, A Salim, A Gretton
arXiv preprint arXiv:1906.04370, 2019
322019
Efficient and principled score estimation with Nystr\" om kernel exponential families
DJ Sutherland, H Strathmann, M Arbel, A Gretton
Proceedings of the Twenty-First International Conference on Artificialá…, 2018
23*2018
Kernel conditional exponential family
M Arbel, A Gretton
Proceedings of the Twenty-First International Conference on Artificialá…, 2018
162018
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 33, 2020
92020
Generalized Energy Based Models
M Arbel, L Zhou, A Gretton
arXiv preprint arXiv:2003.05033, 2020
8*2020
Synchronizing probability measures on rotations via optimal transport
T Birdal, M Arbel, U Simsekli, LJ Guibas
Proceedings of the IEEE/CVF Conference on Computer Vision and Patterná…, 2020
82020
Kernelized Wasserstein Natural Gradient
M Arbel, A Gretton, W Li, G Mont˙far
arXiv preprint arXiv:1910.09652, 2019
72019
Estimating Barycenters of Measures in High Dimensions
S Cohen, M Arbel, MP Deisenroth
arXiv preprint arXiv:2007.07105, 2020
42020
Efficient Wasserstein Natural Gradients for Reinforcement Learning
T Moskovitz, M Arbel, F Huszar, A Gretton
arXiv preprint arXiv:2010.05380, 2020
12020
Methods for Optimization and Regularization of Generative Models
M Arbel
UCL (University College London), 2021
2021
Annealed Flow Transport Monte Carlo
M Arbel, AGDG Matthews, A Doucet
arXiv preprint arXiv:2102.07501, 2021
2021
Deep Reinforcement Learning with Dynamic Optimism
T Moskovitz, J Parker-Holder, A Pacchiano, M Arbel
arXiv preprint arXiv:2102.03765, 2021
2021
The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods
L Thiry, M Arbel, E Belilovsky, E Oyallon
arXiv preprint arXiv:2101.07528, 2021
2021
Il sistema al momento non pu˛ eseguire l'operazione. Riprova pi¨ tardi.
Articoli 1–15