Published in arXiv, 2026
Recommended citation: Pierre Marion and Yu-Han Wu (2026) Understanding diffusion models requires rethinking (again) generalization. arXiv:2605.06077.
Download Paper
Published in arXiv, 2026
Recommended citation: Quentin Berther, Yu-Han Wu, Clément Crepy, Romuald Elie, Klaus Greff & Michael Eli Sander (2026). MIND: Monge Inception Distance for Generative Models Evaluation. arXiv:2605.06797.
Download Paper
Published in arxiv:2510.08409, 2025
Recommended citation: Yu-Han Wu, Quentin Berthet, Gérard Biau, Claire Boyer, Romuald Elie & Pierre Marion (2025). Optimal Stopping in Latent Diffusion Model. arXiv preprint arXiv:2510.08409.
Download Paper | Download Slides
Published in COLT2025, 2025
Recommended citation: Wu, Y. H., Marion, P., Biau, G., & Boyer, C. (2025). Taking a Big Step: Large Learning Rates in Denoising Score Matching Prevent Memorization. Proceedings of Thirty Eighth Conference on Learning Theory, PMLR 291:5718-5756
Download Paper | Download Slides
Published in ICLR2024, 2023
Recommended citation: Pierre Marion, Yu-Han Wu, Michael Eli Sander, & Gerard Biau (2024). Implicit regularization of deep residual networks towards neural ODEs. In The Twelfth International Conference on Learning Representations.
Download Paper
Published in Comptes Rendus. Mathématique, 2022
Recommended citation: Conlon, D., & Wu, Y. H. (2023). More on lines in Euclidean Ramsey theory. Comptes Rendus. Mathématique, 361(G5), 897-901.
Download Paper