collaborators

14 papers

cs.LG2026

Singular perturbations and hierarchical learning in two-layer neural networks

Cédric Gerbelot, Jean-Christophe Mourrat

We study the population gradient flow of an infinitely wide two-layer neural network learning a misspecified single-index model in high dimension. The two layers are optimized join…

math.PR2026

Free energy of non-convex multi-species spin glasses with centered Ising spins

Hong-Bin Chen, Victor Issa, Jean-Christophe Mourrat

We identify the limit free energy of all multi-species spin glasses with centered spins. The result was previously known only under a convexity assumption on the covariance…

math.OC2026

PL conditions do not guarantee convergence of gradient descent-ascent dynamics

Jean-Christophe Mourrat

We give an example of a function satisfying a two-sided Polyak-Lojasiewicz condition but for which a gradient descent-ascent flow line fails to converge to the saddle point, circli…

math.OC2026

Oscillating solutions to the mean-field Langevin descent-ascent flow

Jean-Christophe Mourrat, Loucas Pillaud-Vivien

We present a counterexample to the statement of convergence of the mean-field Langevin descent-ascent flow on . We consider payoff functions that are shaped as a doub…

math.PR2026

One-sided large deviations for the ground-state energy of spin glasses

Hong-Bin Chen, Alice Guionnet, Justin Ko +2

We describe the large deviations above its typical value of the maximal energy of a spin glass with +/-1 spins. Thanks to the relatively explicit description of the rate function w…

math.PR2026

Critical point representation of the mutual information in the sparse stochastic block model

Tomas Dominguez, Jean-Christophe Mourrat

We consider the problem of recovering the community structure in the stochastic block model. We aim to describe the mutual information between the observed network and the actual c…