Multisample flow matching: Straightening flows with minibatch couplings AA Pooladian, H Ben-Hamu, C Domingo-Enrich, B Amos, Y Lipman, ... arXiv preprint arXiv:2304.14772, 2023 | 59 | 2023 |
A mean-field analysis of two-player zero-sum games C Domingo-Enrich, S Jelassi, A Mensch, G Rotskoff, J Bruna Advances in neural information processing systems 33, 20215-20226, 2020 | 57 | 2020 |
Length generalization in arithmetic transformers S Jelassi, S d'Ascoli, C Domingo-Enrich, Y Wu, Y Li, F Charton arXiv preprint arXiv:2306.15400, 2023 | 23 | 2023 |
Outsourcing scalar products and matrix products on privacy-protected unencrypted data stored in untrusted clouds J Domingo-Ferrer, S Ricci, C Domingo-Enrich Information Sciences 436, 320-342, 2018 | 16 | 2018 |
Compress then test: Powerful kernel testing in near-linear time C Domingo-Enrich, R Dwivedi, L Mackey arXiv preprint arXiv:2301.05974, 2023 | 9 | 2023 |
Auditing Differential Privacy in High Dimensions with the Kernel Quantum R\'enyi Divergence C Domingo-Enrich, Y Mroueh arXiv preprint arXiv:2205.13941, 2022 | 9 | 2022 |
On energy-based models with overparametrized shallow neural networks C Domingo-Enrich, A Bietti, E Vanden-Eijnden, J Bruna International Conference on Machine Learning, 2771-2782, 2021 | 8 | 2021 |
Extra-gradient with player sampling for faster convergence in n-player games S Jelassi, C Domingo-Enrich, D Scieur, A Mensch, J Bruna International Conference on Machine Learning, 4736-4745, 2020 | 8* | 2020 |
Average-case acceleration for bilinear games and normal matrices C Domingo-Enrich, F Pedregosa, D Scieur arXiv preprint arXiv:2010.02076, 2020 | 8 | 2020 |
Dual training of energy-based models with overparametrized shallow neural networks C Domingo-Enrich, A Bietti, M Gabrié, J Bruna, E Vanden-Eijnden arXiv preprint arXiv:2107.05134, 2021 | 7 | 2021 |
An explicit expansion of the Kullback-Leibler divergence along its Fisher-Rao gradient flow C Domingo-Enrich, AA Pooladian arXiv preprint arXiv:2302.12229, 2023 | 6 | 2023 |
Extragradient with player sampling for faster Nash equilibrium finding S Jelassi, C Domingo-Enrich, D Scieur, A Mensch, J Bruna Proceedings of the International Conference on Machine Learning, 2020 | 5 | 2020 |
Neural optimal transport with lagrangian costs AA Pooladian, C Domingo-Enrich, RTQ Chen, B Amos arXiv preprint arXiv:2406.00288, 2024 | 4 | 2024 |
Tighter sparse approximation bounds for ReLU neural networks C Domingo-Enrich, Y Mroueh arXiv preprint arXiv:2110.03673, 2021 | 4 | 2021 |
Stochastic optimal control matching C Domingo-Enrich, J Han, B Amos, J Bruna, RTQ Chen arXiv preprint arXiv:2312.02027, 2023 | 3 | 2023 |
Learning with stochastic orders C Domingo-Enrich, Y Schiff, Y Mroueh arXiv preprint arXiv:2205.13684, 2022 | 3 | 2022 |
Simultaneous transport evolution for minimax equilibria on measures C Domingo-Enrich, J Bruna arXiv preprint arXiv:2202.06460, 2022 | 3 | 2022 |
Separation results between fixed-kernel and feature-learning probability metrics C Domingo i Enrich, Y Mroueh Advances in Neural Information Processing Systems 34, 19248-19260, 2021 | 1 | 2021 |
Open Problem: Learning with Variational Objectives on Measures V Cabannes, C Domingo-Enrich arXiv preprint arXiv:2306.11928, 2023 | | 2023 |
Depth and Feature Learning are Provably Beneficial for Neural Network Discriminators C Domingo-Enrich Conference on Learning Theory, 421-447, 2022 | | 2022 |