Lénaïc Chizat

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 29

Top Topics

Top Venues

Publications

Guillaume Wang, Lénaïc Chizat
Open problem: Convergence of single-timescale mean-field Langevin descent-ascent for two-player zero-sum games. COLT (2024)
Pierre Marion, Lénaïc Chizat
Deep linear networks for regression are implicitly regularized towards flat minima. CoRR (2024)
Sebastian Neumayer, Lénaïc Chizat, Michael Unser
On the Effect of Initialization: The Scaling Path of 2-Layer Neural Networks. CoRR (2023)
Lénaïc Chizat, Tomas Vaskevicius
Computational Guarantees for Doubly Entropic Wasserstein Barycenters via Damped Sinkhorn Iterations. CoRR (2023)
Guillaume Wang, Lénaïc Chizat
Local Convergence of Gradient Methods for Min-Max Games under Partial Curvature. CoRR (2023)
Tomas Vaskevicius, Lénaïc Chizat
Computational Guarantees for Doubly Entropic Wasserstein Barycenters. NeurIPS (2023)
Guillaume Wang, Lénaïc Chizat
Local Convergence of Gradient Methods for Min-Max Games: Partial Curvature Generically Suffices. NeurIPS (2023)
Lénaïc Chizat
Doubly Regularized Entropic Wasserstein Barycenters. CoRR (2023)
Lénaïc Chizat, Praneeth Netrapalli
Steering Deep Feature Learning with Backward Aligned Feature Updates. CoRR (2023)
Lénaïc Chizat
Sparse optimization on measures with over-parameterized gradient descent. Math. Program. 194 (1) (2022)
Guillaume Wang, Lénaïc Chizat
An Exponentially Converging Particle Method for the Mixed Nash Equilibrium of Continuous Games. CoRR (2022)
Lénaïc Chizat, Stephen Zhang, Matthieu Heitz, Geoffrey Schiebinger
Trajectory Inference via Mean-field Langevin in Path Space. NeurIPS (2022)
Karl Hajjar, Lénaïc Chizat
Symmetries in the dynamics of wide two-layer neural networks. CoRR (2022)
Lénaïc Chizat, Maria Colombo, Xavier Fernández-Real, Alessio Figalli
Infinite-width limit of deep linear neural networks. CoRR (2022)
Lénaïc Chizat
Mean-Field Langevin Dynamics : Exponential Convergence and Annealing. Trans. Mach. Learn. Res. 2022 (2022)
Lénaïc Chizat, Stephen Zhang, Matthieu Heitz, Geoffrey Schiebinger
Trajectory Inference via Mean-field Langevin in Path Space. CoRR (2022)
Lénaïc Chizat
Convergence Rates of Gradient Methods for Convex Optimization in the Space of Measures. Open J. Math. Optim. 3 (2022)
Karl Hajjar, Lénaïc Chizat, Christophe Giraud
Training Integrable Parameterizations of Deep Neural Networks in the Infinite-Width Limit. CoRR (2021)
Alexis Thibault, Lénaïc Chizat, Charles Dossal, Nicolas Papadakis
Overrelaxed Sinkhorn-Knopp Algorithm for Regularized Optimal Transport. Algorithms 14 (5) (2021)
Kimia Nadjahi, Alain Durmus, Lénaïc Chizat, Soheil Kolouri, Shahin Shahrampour, Umut Simsekli
Statistical and Topological Properties of Sliced Probability Divergences. NeurIPS (2020)
Kimia Nadjahi, Alain Durmus, Lénaïc Chizat, Soheil Kolouri, Shahin Shahrampour, Umut Simsekli
Statistical and Topological Properties of Sliced Probability Divergences. CoRR (2020)
Lénaïc Chizat, Francis R. Bach
Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss. CoRR (2020)
Lénaïc Chizat, Francis R. Bach
Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss. COLT (2020)
Lénaïc Chizat, Pierre Roussillon, Flavien Léger, François-Xavier Vialard, Gabriel Peyré
Faster Wasserstein Distance Estimation with the Sinkhorn Divergence. NeurIPS (2020)
Lénaïc Chizat, Edouard Oyallon, Francis R. Bach
On Lazy Training in Differentiable Programming. NeurIPS (2019)
Jean-Luc Peyrot, Laurent Duval, Frédéric Payan, Lauriane Bouard, Lénaïc Chizat, Sébastien Schneider, Marc Antonini
HexaShrink, an exact scalable framework for hexahedral meshes with attributes and discontinuities: multiresolution rendering and storage of geoscience models. CoRR (2019)
Aude Genevay, Lénaïc Chizat, Francis R. Bach, Marco Cuturi, Gabriel Peyré
Sample Complexity of Sinkhorn Divergences. AISTATS (2019)
Lénaïc Chizat, Francis R. Bach
A Note on Lazy Training in Supervised Differentiable Programming. CoRR (2018)
Lénaïc Chizat, Francis R. Bach
On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport. NeurIPS (2018)