Serial Fault Emulation. - Luc Burgun; Frédéric Reblewski; Gérard Fenelon; Jean Barbier; Olivier Lepape (DAC, 1996)

Compressed sensing of approximately-sparse signals: Phase transitions and optimal reconstruction. - Jean Barbier; Florent Krzakala; Marc Mézard; Lenka Zdeborová (Allerton Conference, 2012)

Robust error correction for real-valued signals via message-passing decoding and spatial coupling. - Jean Barbier; Florent Krzakala; Lenka Zdeborová; Pan Zhang (ITW, 2013)

Compressed sensing and Approximate Message Passing with spatially-coupled Fourier and Hadamard matrices. - Jean Barbier; Florent Krzakala; Christophe Schülke (CoRR, 2013)

The hard-core model on random graphs revisited. - Jean Barbier; Florent Krzakala; Lenka Zdeborová; Pan Zhang (CoRR, 2013)

Replica analysis and approximate message passing decoder for superposition codes. - Jean Barbier; Florent Krzakala (ISIT, 2014)

Error correcting codes and spatial coupling. - Rafah El-Khatib; Jean Barbier; Ayaka Sakata; Rüdiger L. Urbanke (CoRR, 2014)

Statistical physics and approximate message-passing algorithms for sparse linear estimation problems in signal processing and coding theory. - Jean Barbier (CoRR, 2015)

Scampi: a robust approximate message-passing framework for compressive imaging. - Jean Barbier; Eric W. Tramel; Florent Krzakala (CoRR, 2015)

Statistical physics and approximate message passing algorithms for sparse linear estimation problems in signal processing and coding theory. (Physique statistique et algorithme approximé de passage de messages pour les problèmes parcimonieux d'estimation linéaire en traitement du signal et théorie du codage). - Jean Barbier (2015)

The mutual information in random linear estimation. - Jean Barbier; Mohamad Dia; Nicolas Macris; Florent Krzakala (Allerton, 2016)

Proof of threshold saturation for spatially coupled sparse superposition codes. - Jean Barbier; Mohamad Dia; Nicolas Macris (ISIT, 2016)

Threshold saturation of spatially coupled sparse superposition codes for all memoryless channels. - Jean Barbier; Mohamad Dia; Nicolas Macris (ITW, 2016)

Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula. - Jean Barbier; Mohamad Dia; Nicolas Macris; Florent Krzakala; Thibault Lesieur; Lenka Zdeborová (NIPS, 2016)

The layered structure of tensor estimation and its mutual information. - Jean Barbier; Nicolas Macris; Léo Miolane (Allerton, 2017)

I-MMSE relations in random linear estimation and a sub-extensive interpolation method. - Jean Barbier; Nicolas Macris (ISIT, 2017)

Generalized approximate message-passing decoder for universal sparse superposition codes. - Erdem Biyik; Jean Barbier; Mohamad Dia (ISIT, 2017)

The stochastic interpolation method: A simple scheme to prove replica formulas in Bayesian inference. - Jean Barbier; Nicolas Macris (CoRR, 2017)

Phase Transitions, Optimal Errors and Optimality of Message-Passing in Generalized Linear Models. - Jean Barbier; Florent Krzakala; Nicolas Macris; Léo Miolane; Lenka Zdeborová (CoRR, 2017)

Approximate Message-Passing Decoder and Capacity Achieving Sparse Superposition Codes. - Jean Barbier; Florent Krzakala (IEEE Trans. Inf. Theory, 2017)

Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models. - Jean Barbier; Florent Krzakala; Nicolas Macris; Léo Miolane; Lenka Zdeborová (COLT, 2018)

Adaptive Path Interpolation for Sparse Systems: Application to a Simple Censored Block Model. - Jean Barbier; Chun Lam Chan; Nicolas Macris (ISIT, 2018)

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)

Entropy and mutual information in models of deep neural networks. - Marylou Gabrié; Andre Manoel; Clément Luneau; Jean Barbier; Nicolas Macris; Florent Krzakala; Lenka Zdeborová (NeurIPS, 2018)

Rank-one matrix estimation: analysis of algorithmic and information theoretic limits by the spatial coupling method. - Jean Barbier; Mohamad Dia; Nicolas Macris; Florent Krzakala; Lenka Zdeborová (CoRR, 2018)

Concentration of the Matrix-Valued Minimum Mean-Square Error in Optimal Bayesian Inference. - Jean Barbier (CAMSAP, 2019)

Blind Calibration for Sparse Regression: A State Evolution Analysis. - Marylou Gabrié; Jean Barbier; Florent Krzakala; Lenka Zdeborová (CAMSAP, 2019)

Mutual Information for the Stochastic Block Model by the Adaptive Interpolation Method. - Jean Barbier; Chun Lam Chan; Nicolas Macris (ISIT, 2019)

Mutual Information for Low-Rank Even-Order Symmetric Tensor Factorization. - Jean Barbier; Clément Luneau; Nicolas Macris (ITW, 2019)

The adaptive interpolation method for proving replica formulas. Applications to the Curie-Weiss and Wigner spike models. - Jean Barbier; Nicolas Macris (CoRR, 2019)

Overlap matrix concentration in optimal Bayesian inference. - Jean Barbier (CoRR, 2019)

Blind calibration for compressed sensing: State evolution and an online algorithm. - Marylou Gabrié; Jean Barbier; Florent Krzakala; Lenka Zdeborová (CoRR, 2019)

0-1 phase transitions in sparse spiked matrix estimation. - Jean Barbier; Nicolas Macris (CoRR, 2019)

Universal Sparse Superposition Codes With Spatial Coupling and GAMP Decoding. - Jean Barbier; Mohamad Dia; Nicolas Macris (IEEE Trans. Inf. Theory, 2019)

Information-theoretic limits of a multiview low-rank symmetric spiked matrix model. - Jean Barbier; Galen Reeves (ISIT, 2020)

High-dimensional rank-one nonsymmetric matrix decomposition: the spherical case. - Clément Luneau; Nicolas Macris; Jean Barbier (ISIT, 2020)

All-or-nothing statistical and computational phase transitions in sparse spiked matrix estimation. - Jean Barbier; Nicolas Macris; Cynthia Rush (NeurIPS, 2020)

Information theoretic limits of learning a sparse rule. - Clément Luneau; Jean Barbier; Nicolas Macris (NeurIPS, 2020)

Strong replica symmetry in high-dimensional optimal Bayesian inference. - Jean Barbier; Dmitry Panchenko (CoRR, 2020)

Strong replica symmetry for high-dimensional disordered log-concave Gibbs measures. - Jean Barbier; Dmitry Panchenko; Manuel Sáenz (CoRR, 2020)

High-dimensional inference: a statistical mechanics perspective. - Jean Barbier (CoRR, 2020)

Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation. - Jean Barbier; Nicolas Macris; Mohamad Dia; Florent Krzakala (IEEE Trans. Inf. Theory, 2020)

Performance of Bayesian linear regression in a model with mismatch. - Jean Barbier; Wei-Kuo Chen; Dmitry Panchenko; Manuel Sáenz (CoRR, 2021)

Statistical limits of dictionary learning: random matrix theory and the spectral replica method. - Jean Barbier; Nicolas Macris (CoRR, 2021)

Adaptive Path Interpolation Method for Sparse Systems: Application to a Censored Block Model. - Jean Barbier; Chun Lam Chan; Nicolas Macris (IEEE Trans. Inf. Theory, 2021)

Sparse superposition codes under VAMP decoding with generic rotational invariant coding matrices. - Tianqi Hou; Yuhao Liu 005; Teng Fu; Jean Barbier (ISIT, 2022)

Sparse superposition codes with rotational invariant coding matrices for memoryless channels. - Yuhao Liu 005; Teng Fu; Jean Barbier; Tianqi Hou (ITW, 2022)

The price of ignorance: how much does it cost to forget noise structure in low-rank matrix estimation? - Jean Barbier; TianQi Hou; Marco Mondelli; Manuel Sáenz (NeurIPS, 2022)

The mighty force: statistical inference and high-dimensional statistics. - Erik Aurell; Jean Barbier; Aurélien Decelle; Roberto Mulet (CoRR, 2022)

Bayes-optimal limits in structured PCA, and how to reach them. - Jean Barbier; Francesco Camilli; Marco Mondelli; Manuel Sáenz (CoRR, 2022)

Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise. - Teng Fu; Yuhao Liu 005; Jean Barbier; Marco Mondelli; Shansuo Liang; TianQi Hou (ISIT, 2023)

Capacity-Achieving Sparse Regression Codes via Vector Approximate Message Passing. - Yizhou Xu; Yuhao Liu 005; Shansuo Liang; Ting-Yi Wu; Bo Bai 001; Jean Barbier; TianQi Hou (ISIT, 2023)

Fundamental limits of overparametrized shallow neural networks for supervised learning. - Francesco Camilli; Daria Tieplova; Jean Barbier (CoRR, 2023)

A multiscale cavity method for sublinear-rank symmetric matrix factorization. - Jean Barbier; Justin Ko; Anas A. Rahman (CoRR, 2024)

Information limits and Thouless-Anderson-Palmer equations for spiked matrix models with structured noise. - Jean Barbier; Francesco Camilli; Marco Mondelli; Yizhou Xu (CoRR, 2024)

On the phase diagram of extensive-rank symmetric matrix denoising beyond rotational invariance. - Jean Barbier; Francesco Camilli; Justin Ko; Koki Okajima (CoRR, 2024)

Machine learning for cerebral blood vessels' malformations. - Irem Topal; Alexander Cherevko; Yuri Bugay; Maxim A. Shishlenin; Jean Barbier; Deniz Eroglu; Édgar Roldán; Roman Belousov (CoRR, 2024)

Matrix Inference in Growing Rank Regimes. - Farzad Pourkamali; Jean Barbier; Nicolas Macris (IEEE Trans. Inf. Theory, 2024)

Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime. - Francesco Camilli; Daria Tieplova; Eleonora Bergamin; Jean Barbier (COLT, 2025)

Information-theoretic limits and approximate message-passing for high-dimensional time series. - Daria Tieplova; Samriddha Lahiry; Jean Barbier (CoRR, 2025)

Optimal generalisation and learning transition in extensive-width shallow neural networks near interpolation. - Jean Barbier; Francesco Camilli; Minh-Toan Nguyen; Mauro Pastore; Rudy Skerk (CoRR, 2025)

Statistical mechanics of extensive-width Bayesian neural networks near interpolation. - Jean Barbier; Francesco Camilli; Minh-Toan Nguyen; Mauro Pastore; Rudy Skerk (CoRR, 2025)

Generalization performance of narrow one-hidden layer networks in the teacher-student setting. - Jean Barbier; Federica Gerace; Alessandro Ingrosso; Clarissa Lauditi; Enrico M. Malatesta; Gibbs Nwemadji; Rodrigo Pérez Ortiz (CoRR, 2025)