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Marc Mézard

6 papers hereh-index 4183 citations6 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author6

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cond-mat.dis-nn1
  • cond-mat.stat-mech1
same name
  • Marc Mézard — 4 papers, h 3
  • Marc Mézard — 3 papers, h 5
  • Marc Mézard — 3 papers, h 2
  • Marc Mézard — 2 papers, h 3
  • Marc Mézard — 2 papers, h 2
  • Marc Mézard — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20032026
most citedGlass models on Bethe lattices

148 citations · 199 across the 4 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2026

First Learn, Then Memorize: The Spectral Bias of Diffusion Models

Raphaël Urfin, Tony Bonnaire, Giulio Biroli +1

Diffusion models trained on a finite dataset first learn to generate novel, high-quality samples and only much later collapse onto their training set. We identify the mechanism beh…

cs.LG2026

Double Descent and Malign Overfitting in Diffusion Models

Raphaël Urfin, Tony Bonnaire, Giulio Biroli +1

Conventional wisdom in deep learning holds that overparameterization---having more parameters p than training samples n---is benign: larger models generalize better and, even w…

cs.LG2024★ 2 cited

Kernel Density Estimators in Large Dimensions

Giulio Biroli, Marc Mézard

This paper studies Kernel Density Estimation for a high-dimensional distribution ρ(x). Traditional approaches have focused on the limit of large number of data points n and fix…

cs.LG2024★ 48 cited

Dynamical Regimes of Diffusion Models

Giulio Biroli, Tony Bonnaire, Valentin de Bortoli +1

Using statistical physics methods, we study generative diffusion models in the regime where the dimension of space and the number of data are large, and the score function has been…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.