| On Lazy Training in Differentiable Programming L Chizat, E Oyallon, F Bach Advances in Neural Information Processing Systems, 2937-2947, 2019 | 904 | 2019 |
| On the global convergence of gradient descent for over-parameterized models using optimal transport L Chizat, F Bach Advances in Neural Information Processing Systems, 3036-3046, 2018 | 793 | 2018 |
| Scaling algorithms for unbalanced optimal transport problems L Chizat, G Peyré, B Schmitzer, FX Vialard Mathematics of Computation 87 (314), 2563–2609, 2018 | 452* | 2018 |
| Implicit bias of gradient descent for wide two-layer neural networks trained with the logistic loss L Chizat, F Bach Proceedings of Thirty Third Conference on Learning Theory 125, 1305-1338, 2020 | 363 | 2020 |
| Unbalanced optimal transport: Dynamic and Kantorovich formulations L Chizat, G Peyré, B Schmitzer, FX Vialard Journal of Functional Analysis 274 (11), 3090-3123, 2018 | 299* | 2018 |
| Sample complexity of Sinkhorn divergences A Genevay, L Chizat, F Bach, M Cuturi, G Peyré International Conference on Artificial Intelligence and Statistics, 1574-1583, 2019 | 297 | 2019 |
| An interpolating distance between optimal transport and Fisher–Rao metrics L Chizat, G Peyré, B Schmitzer, FX Vialard Foundations of Computational Mathematics 18, 1-44, 2018 | 240 | 2018 |
| Faster Wasserstein distance estimation with the Sinkhorn divergence L Chizat, P Roussillon, F Léger, FX Vialard, G Peyré Advances in Neural Information Processing Systems 33, 2257-2269, 2020 | 163 | 2020 |
| Sparse optimization on measures with over-parameterized gradient descent L Chizat Mathematical Programming, 1-46, 2021 | 109 | 2021 |
| Statistical and topological properties of sliced probability divergences K Nadjahi, A Durmus, L Chizat, S Kolouri, S Shahrampour, U Simsekli Advances in Neural Information Processing Systems 33, 20802-20812, 2020 | 77 | 2020 |
| Mean-field langevin dynamics: Exponential convergence and annealing L Chizat arXiv preprint arXiv:2202.01009, 2022 | 61 | 2022 |
| Quantum entropic regularization of matrix-valued optimal transport G Peyré, L Chizat, FX Vialard, J Solomon European Journal of Applied Mathematics 30 (6), 1079-1102, 2019 | 51* | 2019 |
| Overrelaxed Sinkhorn–Knopp algorithm for regularized optimal transport A Thibault, L Chizat, C Dossal, N Papadakis Algorithms 14 (5), 143, 2021 | 42* | 2021 |
| Unbalanced Optimal Transport: Models, Numerical Methods, Applications L Chizat Université Paris Dauphine - PSL, 2017 | 42 | 2017 |
| A tumor growth model of Hele-Shaw type as a gradient flow S Di Marino, L Chizat ESAIM: Control, Optimisation and Calculus of Variations 26, 103, 2020 | 27* | 2020 |
| Gradient descent on infinitely wide neural networks: Global convergence and generalization F Bach, L Chizat arXiv preprint arXiv:2110.08084, 2021 | 26 | 2021 |
| Convergence rates of gradient methods for convex optimization in the space of measures L Chizat Open Journal of Mathematical Optimization 3, 1-19, 2022 | 25 | 2022 |
| Trajectory Inference via Mean-field Langevin in Path Space L Chizat, S Zhang, M Heitz, G Schiebinger arXiv preprint arXiv:2205.07146, 2022 | 17 | 2022 |
| Infinite‐width limit of deep linear neural networks L Chizat, M Colombo, X Fernández‐Real, A Figalli Communications on Pure and Applied Mathematics, 2022 | 13 | 2022 |
| Doubly regularized entropic Wasserstein barycenters L Chizat arXiv preprint arXiv:2303.11844, 2023 | 11 | 2023 |
