About
I am a second-year PhD student at École Normale Supérieure – PSL in Paris, supervised by Giulio Biroli (ENS) and Marc Mézard (Bocconi University). I am based at the Centre de Sciences des Données and the Laboratoire de Physique de l’ENS (LPENS).
My research aims to build a theoretical understanding of diffusion models, currently the dominant approach to generative AI, using tools from statistical physics.
I was very glad that our work on why diffusion models do not memorize their training data received one of the four Best Paper Awards at NeurIPS 2025.
News
- Looking forward to presenting Double Descent and Malign Overfitting in Diffusion Models at the GdR IASIS day on generative models at ENS Lyon.
- Two new preprints out: First Learn, Then Memorize: The Spectral Bias of Diffusion Models and Weighting Schedules Govern What and When Score-Based Generative Models Learn from Multimodal Data.
- New preprint: Double Descent and Malign Overfitting in Diffusion Models, with Tony Bonnaire, Giulio Biroli and Marc Mézard. Available on arXiv.
Contact
Email. raphael.urfin at phys.ens.psl.eu
Office. Centre de Sciences des Données, 45 rue d'Ulm, 75005 Paris.
Profiles. Google Scholar · OpenReview · GitHub · LinkedIn