most citedPotts Glass on Random Graphs

44 citations · 44 across the 1 of their papers we have counts for

collaborators

6 papers

cond-mat.dis-nn2023

Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective

Davide Ghio, Yatin Dandi, Florent Krzakala +1

Recent years witnessed the development of powerful generative models based on flows, diffusion or autoregressive neural networks, achieving remarkable success in generating data fr…

math.PR2023

Estimating rank-one matrices with mismatched prior and noise: universality and large deviations

Alice Guionnet, Justin Ko, Florent Krzakala +1

We prove a universality result that reduces the free energy of rank-one matrix estimation problems in the setting of mismatched prior and noise to the computation of the free energ…

cs.LG2023

Gibbs Sampling the Posterior of Neural Networks

Giovanni Piccioli, Emanuele Troiani, Lenka Zdeborová

In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation i…

cs.LG2023

High-dimensional Asymptotics of Denoising Autoencoders

Hugo Cui, Lenka Zdeborová

We address the problem of denoising data from a Gaussian mixture using a two-layer non-linear autoencoder with tied weights and a skip connection. We consider the high-dimensional…

math.PR2023

Maximally-stable Local Optima in Random Graphs and Spin Glasses: Phase Transitions and Universality

Yatin Dandi, David Gamarnik, Lenka Zdeborová

We consider -stable local optima of Ising spin glass models, defined as spin configurations such that for nearly all of the spins, flipping their values results in increasing en…

cond-mat.dis-nn200744 cited

Potts Glass on Random Graphs

Florent Krzakala, Lenka Zdeborová

We solve the q-state Potts model with anti-ferromagnetic interactions on large random lattices of finite coordination. Due to the frustration induced by the large loops and to the…