Generalized linear models (GLMs) are used in high-dimensional machine learning,
statistics, communications, and signal processing. In this paper we analyze GLMs when the …

Unsourced random-access (U-RA) is a type of grant-free random access with a virtually
unlimited number of users, of which only a certain number K a are active on the same time …

In recent years important progress has been achieved towards proving the validity of the
replica predictions for the (asymptotic) mutual information (or “free energy”) in Bayesian …

In phase retrieval we want to recover an unknown signal $\boldsymbol x\in\mathbb C^ d $
from $ n $ quadratic measurements of the form $ y_i=|⟨\boldsymbol a_i,\boldsymbol x⟩|^ 2+ …

Heuristic tools from statistical physics have been used in the past to compute the optimal
learning and generalization errors in the teacher-student scenario in multi-layer neural …

Fundamental barriers to high-dimensional regression with convex penalties Page 1 The
Annals of Statistics 2022, Vol. 50, No. 1, 170–196 https://doi.org/10.1214/21-AOS2100 © …

This paper studies the optimal achievable performance of compressed sensing based
unsourced random-access communication over the real AWGN channel." Unsourced" …

In this contribution we give a pedagogic introduction to the newly introduced adaptive
interpolation method to prove in a simple and unified way replica formulas for Bayesian …

We determine statistical and computational limits for estimation of a rank-one matrix (the
spike) corrupted by an additive gaussian noise matrix, in a sparse limit, where the …

Deep generative priors offer powerful models for complex-structured data, such as images,
audio, and text. Using these priors in inverse problems typically requires estimating the input …