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Aude Genevay
Aude Genevay
Applied Scientist, Amazon
Dirección de correo verificada de amazon.com - Página principal
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Citado por
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Año
Learning generative models with Sinkhorn divergences
A Genevay, G Peyré, M Cuturi
International Conference on Artificial Intelligence and Statistics. 2018., 2018
7212018
Stochastic optimization for large-scale optimal transport
A Genevay, M Cuturi, G Peyré, F Bach
Advances in neural information processing systems 29, 2016
5462016
Sample complexity of Sinkhorn divergences
A Genevay, L Chizat, F Bach, M Cuturi, G Peyré
International Conference on Artificial Intelligence and Statistics. 2018., 2019
3162019
Large-scale wasserstein gradient flows
P Mokrov, A Korotin, L Li, A Genevay, JM Solomon, E Burnaev
Advances in Neural Information Processing Systems 34, 15243-15256, 2021
792021
Do neural optimal transport solvers work? a continuous wasserstein-2 benchmark
A Korotin, L Li, A Genevay, JM Solomon, A Filippov, E Burnaev
Advances in neural information processing systems 34, 14593-14605, 2021
742021
GAN and VAE from an optimal transport point of view
A Genevay, G Peyré, M Cuturi
arXiv preprint arXiv:1706.01807, 2017
712017
Entropy-Regularized Optimal Transport for Machine Learning
A Genevay
PhD thesis, PSL University., 2019
632019
Continuous regularized wasserstein barycenters
L Li, A Genevay, M Yurochkin, JM Solomon
Advances in Neural Information Processing Systems 33, 17755-17765, 2020
502020
Differentiable deep clustering with cluster size constraints
A Genevay, G Dulac-Arnold, JP Vert
arXiv preprint arXiv:1910.09036, 2019
502019
Transfer Learning for User Adaptation in Spoken Dialogue Systems.
A Genevay, R Laroche
AAMAS, 975-983, 2016
332016
Sinkhorn-autodiff: Tractable wasserstein learning of generative models
A Genevay, G Peyré, M Cuturi
arXiv preprint arXiv:1706.00292 7 (8), 2017
312017
Wasserstein measure coresets
S Claici, A Genevay, J Solomon
arXiv preprint arXiv:1805.07412, 2018
22*2018
Improving approximate optimal transport distances using quantization
G Beugnot, A Genevay, K Greenewald, J Solomon
Uncertainty in artificial intelligence, 290-300, 2021
102021
Entropy-Regularized Optimal Transport for Machine Learning.(Régularisation Entropique du Transport Optimal pour le Machine Learning).
A Genevay
PSL Research University, Paris, France, 2019
22019
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Artículos 1–14