Learning generative models with Sinkhorn divergences A Genevay, G Peyré, M Cuturi International Conference on Artificial Intelligence and Statistics. 2018., 2018 | 721 | 2018 |
Stochastic optimization for large-scale optimal transport A Genevay, M Cuturi, G Peyré, F Bach Advances in neural information processing systems 29, 2016 | 546 | 2016 |
Sample complexity of Sinkhorn divergences A Genevay, L Chizat, F Bach, M Cuturi, G Peyré International Conference on Artificial Intelligence and Statistics. 2018., 2019 | 316 | 2019 |
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 | 79 | 2021 |
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 | 74 | 2021 |
GAN and VAE from an optimal transport point of view A Genevay, G Peyré, M Cuturi arXiv preprint arXiv:1706.01807, 2017 | 71 | 2017 |
Entropy-Regularized Optimal Transport for Machine Learning A Genevay PhD thesis, PSL University., 2019 | 63 | 2019 |
Continuous regularized wasserstein barycenters L Li, A Genevay, M Yurochkin, JM Solomon Advances in Neural Information Processing Systems 33, 17755-17765, 2020 | 50 | 2020 |
Differentiable deep clustering with cluster size constraints A Genevay, G Dulac-Arnold, JP Vert arXiv preprint arXiv:1910.09036, 2019 | 50 | 2019 |
Transfer Learning for User Adaptation in Spoken Dialogue Systems. A Genevay, R Laroche AAMAS, 975-983, 2016 | 33 | 2016 |
Sinkhorn-autodiff: Tractable wasserstein learning of generative models A Genevay, G Peyré, M Cuturi arXiv preprint arXiv:1706.00292 7 (8), 2017 | 31 | 2017 |
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 | 10 | 2021 |
Entropy-Regularized Optimal Transport for Machine Learning.(Régularisation Entropique du Transport Optimal pour le Machine Learning). A Genevay PSL Research University, Paris, France, 2019 | 2 | 2019 |