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20232026
most citedNonlinear spiked covariance matrices and signal propagation in deep neural networks

1 citations · 1 across the 7 of their papers we have counts for

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math.ST2025

When does Gaussian equivalence fail and how to fix it: Non-universal behavior of random features with quadratic scaling

Garrett G. Wen, Hong Hu, Yue M. Lu +2

A major effort in modern high-dimensional statistics has been devoted to the analysis of linear predictors trained on nonlinear feature embeddings via empirical risk minimization (…

math.ST2025

Dynamical mean-field analysis of adaptive Langevin diffusions: Replica-symmetric fixed point and empirical Bayes

Zhou Fan, Justin Ko, Bruno Loureiro +2

In many applications of statistical estimation via sampling, one may wish to sample from a high-dimensional target distribution that is adaptively evolving to the samples already s…

math.ST2025

Dynamical mean-field analysis of adaptive Langevin diffusions: Propagation-of-chaos and convergence of the linear response

Zhou Fan, Justin Ko, Bruno Loureiro +2

Motivated by an application to empirical Bayes learning in high-dimensional regression, we study a class of Langevin diffusions in a system with random disorder, where the drift co…

math.ST2024

Asymptotic mutual information in quadratic estimation problems over compact groups

Kaylee Y. Yang, Timothy L. H. Wee, Zhou Fan

Motivated by applications to group synchronization and quadratic assignment on random data, we study a general problem of Bayesian inference of an unknown ``signal'' belonging to a…

math.ST2023

Mean-field variational inference with the TAP free energy: Geometric and statistical properties in linear models

Michael Celentano, Zhou Fan, Licong Lin +1

We study mean-field variational inference in a Bayesian linear model when the sample size n is comparable to the dimension p. In high dimensions, the common approach of minimizing…