The Mutual Information in Random Linear Estimation Beyond i.i.d. Matrices. - Jean Barbier; Nicolas Macris; Antoine Maillard; Florent Krzakala (ISIT, 2018)

The committee machine: Computational to statistical gaps in learning a two-layers neural network. - Benjamin Aubin; Antoine Maillard; Jean Barbier; Florent Krzakala; Nicolas Macris; Lenka Zdeborová (NeurIPS, 2018)

High-temperature Expansions and Message Passing Algorithms. - Antoine Maillard; Laura Foini; Alejandro Lage Castellanos; Florent Krzakala; Marc Mézard; Lenka Zdeborová (CoRR, 2019)

Landscape Complexity for the Empirical Risk of Generalized Linear Models. - Antoine Maillard; Gérard Ben Arous; Giulio Biroli (MSML, 2020)

Phase retrieval in high dimensions: Statistical and computational phase transitions. - Antoine Maillard; Bruno Loureiro; Florent Krzakala; Lenka Zdeborová (NeurIPS, 2020)

Construction of optimal spectral methods in phase retrieval. - Antoine Maillard; Florent Krzakala; Yue M. Lu; Lenka Zdeborová (MSML, 2021)

Perturbative construction of mean-field equations in extensive-rank matrix factorization and denoising. - Antoine Maillard; Florent Krzakala; Marc Mézard; Lenka Zdeborová (CoRR, 2021)

The Spiked Matrix Model With Generative Priors. - Benjamin Aubin; Bruno Loureiro; Antoine Maillard; Florent Krzakala; Lenka Zdeborová (IEEE Trans. Inf. Theory, 2021)

Optimal denoising of rotationally invariant rectangular matrices. - Emanuele Troiani; Vittorio Erba; Florent Krzakala; Antoine Maillard; Lenka Zdeborová (MSML, 2022)

A remark on Kashin's discrepancy argument and partial coloring in the Komlós conjecture. - Afonso S. Bandeira; Antoine Maillard; Nikita Zhivotovskiy (CoRR, 2022)

On free energy barriers in Gaussian priors and failure of MCMC for high-dimensional unimodal distributions. - Afonso S. Bandeira; Antoine Maillard; Richard Nickl; Sven Wang (CoRR, 2022)

Injectivity of ReLU networks: perspectives from statistical physics. - Antoine Maillard; Afonso S. Bandeira; David Belius; Ivan Dokmanic; Shuta Nakajima (CoRR, 2023)

Fitting an ellipsoid to a quadratic number of random points. - Afonso S. Bandeira; Antoine Maillard; Shahar Mendelson; Elliot Paquette (CoRR, 2023)

Exact threshold for approximate ellipsoid fitting of random points. - Antoine Maillard; Afonso S. Bandeira (CoRR, 2023)

Phase Retrieval: From Computational Imaging to Machine Learning: A tutorial. - Jonathan Dong; Lorenzo Valzania; Antoine Maillard; Thanh-An Pham; Sylvain Gigan; Michael Unser (IEEE Signal Process. Mag., 2023)

Bayes-optimal learning of an extensive-width neural network from quadratically many samples. - Antoine Maillard; Emanuele Troiani; Simon Martin 008; Florent Krzakala; Lenka Zdeborová (NeurIPS, 2024)

Average-case matrix discrepancy: satisfiability bounds. - Antoine Maillard (CoRR, 2024)

Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-dimensional Tokens. - Vittorio Erba; Emanuele Troiani; Luca Biggio; Antoine Maillard; Lenka Zdeborová (CoRR, 2024)

Fitting an Ellipsoid to Random Points: Predictions Using the Replica Method. - Antoine Maillard; Dmitriy Kunisky (IEEE Trans. Inf. Theory, 2024)

Fundamental Limits of Matrix Sensing: Exact Asymptotics, Universality, and Applications. - Yizhou Xu; Antoine Maillard; Lenka Zdeborová; Florent Krzakala (COLT, 2025)

Randomstrasse101: Open Problems of 2024. - Afonso S. Bandeira; Anastasia Kireeva; Antoine Maillard; Almut Rödder (CoRR, 2025)