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ORCIDJean Barbier
Person information
- affiliation: International Center for Theoretical Physics, Trieste, Italy
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2020 – today
- 2024
[i52]Jean Barbier, Justin Ko, Anas A. Rahman:
A multiscale cavity method for sublinear-rank symmetric matrix factorization. CoRR abs/2403.07189 (2024)- [i51]Jean Barbier, Francesco Camilli, Marco Mondelli, Yizhou Xu:
Information limits and Thouless-Anderson-Palmer equations for spiked matrix models with structured noise. CoRR abs/2405.20993 (2024) - 2023
- [c29]Yizhou Xu, Yuhao Liu, Shansuo Liang, Ting-Yi Wu, Bo Bai, Jean Barbier, TianQi Hou:
Capacity-Achieving Sparse Regression Codes via Vector Approximate Message Passing. ISIT 2023: 785-790 - [c28]Teng Fu, Yuhao Liu, Jean Barbier, Marco Mondelli, Shansuo Liang, TianQi Hou:
Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise. ISIT 2023: 1178-1183 - [i50]Teng Fu, Yuhao Liu, Jean Barbier, Marco Mondelli, Shansuo Liang, TianQi Hou:
Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise. CoRR abs/2302.03306 (2023) - [i49]Yizhou Xu, Yuhao Liu, Shansuo Liang, Ting-Yi Wu, Bo Bob Bai, Jean Barbier, TianQi Hou:
Capacity-Achieving Sparse Regression Codes via Vector Approximate Message Passing. CoRR abs/2303.08406 (2023) - [i48]Farzad Pourkamali, Jean Barbier, Nicolas Macris:
Matrix Inference in Growing Rank Regimes. CoRR abs/2306.01412 (2023) - [i47]Francesco Camilli, Daria Tieplova, Jean Barbier:
Fundamental limits of overparametrized shallow neural networks for supervised learning. CoRR abs/2307.05635 (2023) - 2022
- [c27]Tianqi Hou, Yuhao Liu, Teng Fu, Jean Barbier:
Sparse superposition codes under VAMP decoding with generic rotational invariant coding matrices. ISIT 2022: 1372-1377 - [c26]Yuhao Liu, Teng Fu, Jean Barbier, Tianqi Hou:
Sparse superposition codes with rotational invariant coding matrices for memoryless channels. ITW 2022: 267-272 - [c25]Jean Barbier, TianQi Hou, Marco Mondelli, Manuel Sáenz:
The price of ignorance: how much does it cost to forget noise structure in low-rank matrix estimation? NeurIPS 2022 - [i46]Tianqi Hou, Yuhao Liu, Teng Fu, Jean Barbier:
Sparse superposition codes under VAMP decoding with generic rotational invariant coding matrices. CoRR abs/2202.04541 (2022) - [i45]Erik Aurell, Jean Barbier, Aurélien Decelle
, Roberto Mulet:
The mighty force: statistical inference and high-dimensional statistics. CoRR abs/2205.00750 (2022) - [i44]Yuhao Liu, Teng Fu, Jean Barbier, Tianqi Hou:
Sparse superposition codes with rotational invariant coding matrices for memoryless channels. CoRR abs/2205.08980 (2022) - [i43]Jean Barbier, Tianqi Hou, Marco Mondelli, Manuel Sáenz:
The price of ignorance: how much does it cost to forget noise structure in low-rank matrix estimation? CoRR abs/2205.10009 (2022) - [i42]Jean Barbier, Francesco Camilli, Marco Mondelli, Manuel Sáenz:
Bayes-optimal limits in structured PCA, and how to reach them. CoRR abs/2210.01237 (2022) - 2021
- [j4]Jean Barbier, Chun Lam Chan, Nicolas Macris:
Adaptive Path Interpolation Method for Sparse Systems: Application to a Censored Block Model. IEEE Trans. Inf. Theory 67(4): 2093-2114 (2021) - [i41]Jean Barbier, Wei-Kuo Chen, Dmitry Panchenko, Manuel Sáenz:
Performance of Bayesian linear regression in a model with mismatch. CoRR abs/2107.06936 (2021) - [i40]Jean Barbier, Nicolas Macris:
Statistical limits of dictionary learning: random matrix theory and the spectral replica method. CoRR abs/2109.06610 (2021) - 2020
- [j3]Jean Barbier, Nicolas Macris, Mohamad Dia, Florent Krzakala:
Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation. IEEE Trans. Inf. Theory 66(7): 4270-4303 (2020) - [c24]Clément Luneau, Nicolas Macris, Jean Barbier:
High-dimensional rank-one nonsymmetric matrix decomposition: the spherical case. ISIT 2020: 2646-2651 - [c23]Jean Barbier, Galen Reeves:
Information-theoretic limits of a multiview low-rank symmetric spiked matrix model. ISIT 2020: 2771-2776 - [c22]Jean Barbier, Nicolas Macris, Cynthia Rush:
All-or-nothing statistical and computational phase transitions in sparse spiked matrix estimation. NeurIPS 2020 - [c21]Clément Luneau, Jean Barbier, Nicolas Macris:
Information theoretic limits of learning a sparse rule. NeurIPS 2020 - [i39]Clément Luneau, Nicolas Macris, Jean Barbier:
High-dimensional rank-one nonsymmetric matrix decomposition: the spherical case. CoRR abs/2004.06975 (2020) - [i38]Jean Barbier, Dmitry Panchenko:
Strong replica symmetry in high-dimensional optimal Bayesian inference. CoRR abs/2005.03115 (2020) - [i37]Jean Barbier, Galen Reeves:
Information-theoretic limits of a multiview low-rank symmetric spiked matrix model. CoRR abs/2005.08017 (2020) - [i36]Jean Barbier, Nicolas Macris, Cynthia Rush:
All-or-nothing statistical and computational phase transitions in sparse spiked matrix estimation. CoRR abs/2006.07971 (2020) - [i35]Clément Luneau, Jean Barbier, Nicolas Macris:
Information theoretic limits of learning a sparse rule. CoRR abs/2006.11313 (2020) - [i34]Jean Barbier, Dmitry Panchenko, Manuel Sáenz:
Strong replica symmetry for high-dimensional disordered log-concave Gibbs measures. CoRR abs/2009.12939 (2020) - [i33]Jean Barbier:
High-dimensional inference: a statistical mechanics perspective. CoRR abs/2010.14863 (2020)
2010 – 2019
- 2019
- [j2]Jean Barbier, Mohamad Dia, Nicolas Macris:
Universal Sparse Superposition Codes With Spatial Coupling and GAMP Decoding. IEEE Trans. Inf. Theory 65(9): 5618-5642 (2019) - [c20]Jean Barbier:
Concentration of the Matrix-Valued Minimum Mean-Square Error in Optimal Bayesian Inference. CAMSAP 2019: 644-648 - [c19]Marylou Gabrié, Jean Barbier, Florent Krzakala, Lenka Zdeborová:
Blind Calibration for Sparse Regression: A State Evolution Analysis. CAMSAP 2019: 649-653 - [c18]Jean Barbier, Chun Lam Chan, Nicolas Macris:
Mutual Information for the Stochastic Block Model by the Adaptive Interpolation Method. ISIT 2019: 405-409 - [c17]Jean Barbier, Clément Luneau, Nicolas Macris:
Mutual Information for Low-Rank Even-Order Symmetric Tensor Factorization. ITW 2019: 1-5 - [i32]Jean Barbier, Nicolas Macris:
The adaptive interpolation method for proving replica formulas. Applications to the Curie-Weiss and Wigner spike models. CoRR abs/1901.06516 (2019) - [i31]Jean Barbier, Chun Lam Chan, Nicolas Macris:
Mutual Information for the Stochastic Block Model by the Adaptive Interpolation Method. CoRR abs/1902.07273 (2019) - [i30]Jean Barbier:
Overlap matrix concentration in optimal Bayesian inference. CoRR abs/1904.02808 (2019) - [i29]Jean Barbier, Clément Luneau, Nicolas Macris:
Mutual Information for Low-Rank Even-Order Symmetric Tensor Factorization. CoRR abs/1904.04565 (2019) - [i28]Jean Barbier:
Concentration of the matrix-valued minimum mean-square error in optimal Bayesian inference. CoRR abs/1907.07103 (2019) - [i27]Marylou Gabrié, Jean Barbier, Florent Krzakala, Lenka Zdeborová:
Blind calibration for compressed sensing: State evolution and an online algorithm. CoRR abs/1910.00285 (2019) - [i26]Jean Barbier, Nicolas Macris:
0-1 phase transitions in sparse spiked matrix estimation. CoRR abs/1911.05030 (2019) - 2018
- [c16]Jean Barbier, Florent Krzakala, Nicolas Macris, Léo Miolane, Lenka Zdeborová:
Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models. COLT 2018: 728-731 - [c15]Jean Barbier, Nicolas Macris, Antoine Maillard, Florent Krzakala:
The Mutual Information in Random Linear Estimation Beyond i.i.d. Matrices. ISIT 2018: 1390-1394 - [c14]Jean Barbier, Chun Lam Chan, Nicolas Macris:
Adaptive Path Interpolation for Sparse Systems: Application to a Simple Censored Block Model. ISIT 2018: 1879-1883 - [c13]Marylou Gabrié, Andre Manoel, Clément Luneau, Jean Barbier, Nicolas Macris, Florent Krzakala, Lenka Zdeborová:
Entropy and mutual information in models of deep neural networks. NeurIPS 2018: 1826-1836 - [c12]Benjamin Aubin, Antoine Maillard, Jean Barbier, Florent Krzakala, Nicolas Macris, Lenka Zdeborová:
The committee machine: Computational to statistical gaps in learning a two-layers neural network. NeurIPS 2018: 3227-3238 - [i25]Jean Barbier, Nicolas Macris, Antoine Maillard, Florent Krzakala:
The Mutual Information in Random Linear Estimation Beyond i.i.d. Matrices. CoRR abs/1802.08963 (2018) - [i24]Marylou Gabrié, Andre Manoel, Clément Luneau, Jean Barbier, Nicolas Macris, Florent Krzakala, Lenka Zdeborová:
Entropy and mutual information in models of deep neural networks. CoRR abs/1805.09785 (2018) - [i23]Jean Barbier, Chun Lam Chan, Nicolas Macris:
Adaptive Path Interpolation for Sparse Systems: Application to a Simple Censored Block Model. CoRR abs/1806.05121 (2018) - [i22]Benjamin Aubin, Antoine Maillard, Jean Barbier, Florent Krzakala, Nicolas Macris, Lenka Zdeborová:
The committee machine: Computational to statistical gaps in learning a two-layers neural network. CoRR abs/1806.05451 (2018) - [i21]Jean Barbier, Mohamad Dia, Nicolas Macris, Florent Krzakala, Lenka Zdeborová:
Rank-one matrix estimation: analysis of algorithmic and information theoretic limits by the spatial coupling method. CoRR abs/1812.02537 (2018) - 2017
- [j1]Jean Barbier, Florent Krzakala:
Approximate Message-Passing Decoder and Capacity Achieving Sparse Superposition Codes. IEEE Trans. Inf. Theory 63(8): 4894-4927 (2017) - [c11]Jean Barbier, Nicolas Macris, Léo Miolane:
The layered structure of tensor estimation and its mutual information. Allerton 2017: 1056-1063 - [c10]Erdem Biyik, Jean Barbier, Mohamad Dia:
Generalized approximate message-passing decoder for universal sparse superposition codes. ISIT 2017: 1593-1597 - [c9]Jean Barbier, Nicolas Macris:
I-MMSE relations in random linear estimation and a sub-extensive interpolation method. ISIT 2017: 2108-2112 - [i20]Erdem Biyik, Jean Barbier, Mohamad Dia:
Generalized Approximate Message-Passing Decoder for Universal Sparse Superposition Codes. CoRR abs/1701.03590 (2017) - [i19]Jean Barbier, Nicolas Macris, Mohamad Dia, Florent Krzakala:
Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation. CoRR abs/1701.05823 (2017) - [i18]Jean Barbier, Nicolas Macris:
I-MMSE relations in random linear estimation and a sub-extensive interpolation method. CoRR abs/1704.04158 (2017) - [i17]Jean Barbier, Nicolas Macris:
The stochastic interpolation method: A simple scheme to prove replica formulas in Bayesian inference. CoRR abs/1705.02780 (2017) - [i16]Jean Barbier, Mohamad Dia, Nicolas Macris:
Universal Sparse Superposition Codes with Spatial Coupling and GAMP Decoding. CoRR abs/1707.04203 (2017) - [i15]Jean Barbier, Florent Krzakala, Nicolas Macris, Léo Miolane, Lenka Zdeborová:
Phase Transitions, Optimal Errors and Optimality of Message-Passing in Generalized Linear Models. CoRR abs/1708.03395 (2017) - [i14]Jean Barbier, Nicolas Macris, Léo Miolane:
The Layered Structure of Tensor Estimation and its Mutual Information. CoRR abs/1709.10368 (2017) - 2016
- [c8]Jean Barbier, Mohamad Dia, Nicolas Macris, Florent Krzakala:
The mutual information in random linear estimation. Allerton 2016: 625-632 - [c7]Jean Barbier, Mohamad Dia, Nicolas Macris:
Proof of threshold saturation for spatially coupled sparse superposition codes. ISIT 2016: 1173-1177 - [c6]Jean Barbier, Mohamad Dia, Nicolas Macris:
Threshold saturation of spatially coupled sparse superposition codes for all memoryless channels. ITW 2016: 76-80 - [c5]Jean Barbier, Mohamad Dia, Nicolas Macris, Florent Krzakala, Thibault Lesieur, Lenka Zdeborová:
Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula. NIPS 2016: 424-432 - [i13]Jean Barbier, Mohamad Dia, Nicolas Macris:
Proof of Threshold Saturation for Spatially Coupled Sparse Superposition Codes. CoRR abs/1603.01817 (2016) - [i12]Jean Barbier, Mohamad Dia, Nicolas Macris:
Threshold Saturation of Spatially Coupled Sparse Superposition Codes for All Memoryless Channels. CoRR abs/1603.04591 (2016) - [i11]Jean Barbier, Mohamad Dia, Nicolas Macris, Florent Krzakala, Thibault Lesieur, Lenka Zdeborová:
Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula. CoRR abs/1606.04142 (2016) - [i10]Jean Barbier, Mohamad Dia, Nicolas Macris, Florent Krzakala:
The Mutual Information in Random Linear Estimation. CoRR abs/1607.02335 (2016) - 2015
- [b1]Jean Barbier:
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). Paris Diderot University, France, 2015 - [i9]Jean Barbier, Florent Krzakala:
Approximate message-passing decoder and capacity-achieving sparse superposition codes. CoRR abs/1503.08040 (2015) - [i8]Jean Barbier:
Statistical physics and approximate message-passing algorithms for sparse linear estimation problems in signal processing and coding theory. CoRR abs/1511.01650 (2015) - [i7]Jean Barbier, Eric W. Tramel, Florent Krzakala:
Scampi: a robust approximate message-passing framework for compressive imaging. CoRR abs/1511.05860 (2015) - 2014
- [c4]Jean Barbier, Florent Krzakala:
Replica analysis and approximate message passing decoder for superposition codes. ISIT 2014: 1494-1498 - [i6]Jean Barbier, Florent Krzakala:
Replica Analysis and Approximate Message Passing Decoder for Superposition Codes. CoRR abs/1403.8024 (2014) - [i5]Rafah El-Khatib, Jean Barbier, Ayaka Sakata, Rüdiger L. Urbanke:
Error correcting codes and spatial coupling. CoRR abs/1409.7465 (2014) - 2013
- [c3]Jean Barbier, Florent Krzakala, Lenka Zdeborová, Pan Zhang:
Robust error correction for real-valued signals via message-passing decoding and spatial coupling. ITW 2013: 1-5 - [i4]Jean Barbier, Florent Krzakala, Lenka Zdeborová, Pan Zhang:
Robust error correction for real-valued signals via message-passing decoding and spatial coupling. CoRR abs/1304.6599 (2013) - [i3]Jean Barbier, Florent Krzakala, Lenka Zdeborová, Pan Zhang:
The hard-core model on random graphs revisited. CoRR abs/1306.4121 (2013) - [i2]Jean Barbier, Florent Krzakala, Christophe Schülke:
Compressed sensing and Approximate Message Passing with spatially-coupled Fourier and Hadamard matrices. CoRR abs/1312.1740 (2013) - 2012
- [c2]Jean Barbier, Florent Krzakala, Marc Mézard, Lenka Zdeborová:
Compressed sensing of approximately-sparse signals: Phase transitions and optimal reconstruction. Allerton Conference 2012: 800-807 - [i1]Jean Barbier, Florent Krzakala, Marc Mézard, Lenka Zdeborová:
Compressed Sensing of Approximately-Sparse Signals: Phase Transitions and Optimal Reconstruction. CoRR abs/1207.2079 (2012)
1990 – 1999
- 1996
- [c1]Luc Burgun, Frédéric Reblewski, Gérard Fenelon, Jean Barbier, Olivier Lepape:
Serial Fault Emulation. DAC 1996: 801-806
Coauthor Index
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