Portrait of Samuel Hurault

Researcher in applied mathematics & machine learning

Samuel Hurault

CR CNRS · MMSID team, LIGM, Université Gustave Eiffel

About Me

I am a CNRS researcher in the MMSID team at LIGM (Université Gustave Eiffel, France). My research focuses on generative modeling, image inverse problems, and optimization, with a particular interest in the theoretical analysis of denoising diffusion models. I am also a core developer of the Python library DeepInv, which provides a unified framework for solving inverse problems with deep neural networks.

Previously, I was a postdoctoral researcher at ENS Paris with Gabriel Peyré, and I obtained my Ph.D. from Université de Bordeaux, co-supervised by Nicolas Papadakis and Arthur Leclaire.

Research interests

  • Diffusion models & Flow Matching
  • Drifting models
  • Image inverse problems
  • Proximal algorithms
  • Large Language Models

Selected work

Recent publications

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