Marion, Pierre

12 publications

ICLR 2025 Attention Layers Provably Solve Single-Location Regression Pierre Marion, Raphaël Berthier, Gérard Biau, Claire Boyer

NeurIPS 2025 Attention-Based Clustering Rodrigo Maulen-Soto, Pierre Marion, Claire Boyer

AISTATS 2025 Implicit Diffusion: Efficient Optimization Through Stochastic Sampling Pierre Marion, Anna Korba, Peter Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet

NeurIPS 2025 Large Stepsizes Accelerate Gradient Descent for Regularized Logistic Regression Jingfeng Wu, Pierre Marion, Peter Bartlett

JMLR 2025 Scaling ResNets in the Large-Depth Regime Pierre Marion, Adeline Fermanian, Gérard Biau, Jean-Philippe Vert

COLT 2025 Taking a Big Step: Large Learning Rates in Denoising Score Matching Prevent Memorization Yu-Han Wu, Pierre Marion, Gérard Biau, Claire Boyer

NeurIPS 2024 Deep Linear Networks for Regression Are Implicitly Regularized Towards Flat Minima Pierre Marion, Lénaïc Chizat

ICMLW 2024 Implicit Diffusion: Efficient Optimization Through Stochastic Sampling Pierre Marion, Anna Korba, Peter Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet

ICLR 2024 Implicit Regularization of Deep Residual Networks Towards Neural ODEs Pierre Marion, Yu-Han Wu, Michael Eli Sander, Gérard Biau

NeurIPS 2023 Generalization Bounds for Neural Ordinary Differential Equations and Deep Residual Networks Pierre Marion

NeurIPS 2023 Leveraging the Two-Timescale Regime to Demonstrate Convergence of Neural Networks Pierre Marion, Raphaël Berthier

NeurIPS 2021 Framing RNN as a Kernel Method: A Neural ODE Approach Adeline Fermanian, Pierre Marion, Jean-Philippe Vert, Gérard Biau