Basins of Attraction in a Perception-like Neural Network. - Werner Krauth; Marc Mézard; Jean-Pierre Nadal (Complex Syst., 1988)

Learning algorithms in neural networks: recent results. - Marc Mézard (NATO Neurocomputing, 1989)

On The Mean Field Theory of Random Heteropolymers. - Silvio Franz; Marc Mézard; Giorgio Parisi (Int. J. Neural Syst., 1992)

Alternative solutions to diluted p-spin models and XORSAT problems - Marc Mézard; Federico Ricci-Tersenghi; Riccardo Zecchina (CoRR, 2002)

Constraint Satisfaction by Survey Propagation - Alfredo Braunstein; Marc Mézard; Martin Weigt; Riccardo Zecchina (CoRR, 2002)

Threshold values of Random K-SAT from the cavity method - Stephan Mertens; Marc Mézard; Riccardo Zecchina (CoRR, 2003)

Clustering of solutions in the random satisfiability problem - Marc Mézard; Thierry Mora; Riccardo Zecchina (CoRR, 2005)

Pairs of SAT Assignment in Random Boolean Formulae - Hervé Daudé; Marc Mézard; Thierry Mora; Riccardo Zecchina (CoRR, 2005)

The theoretical capacity of the Parity Source Coder - Stefano Ciliberti; Marc Mézard (CoRR, 2005)

Landscape of solutions in constraint satisfaction problems - Marc Mézard; Matteo Palassini; Olivier Rivoire (CoRR, 2005)

Survey propagation: An algorithm for satisfiability. - Alfredo Braunstein; Marc Mézard; Riccardo Zecchina (Random Struct. Algorithms, 2005)

Constraint Satisfaction by Survey Propagation. - Alfredo Braunstein; Marc Mézard; Martin Weigt; Riccardo Zecchina (Computational Complexity and Statistical Physics, 2006)

The number of matchings in random graphs - Lenka Zdeborová; Marc Mézard (CoRR, 2006)

Geometrical organization of solutions to random linear Boolean equations - Thierry Mora; Marc Mézard (CoRR, 2006)

Threshold values of random K-SAT from the cavity method. - Stephan Mertens; Marc Mézard; Riccardo Zecchina (Random Struct. Algorithms, 2006)

Hard constraint satisfaction problems - Lenka Zdeborová; Marc Mézard (CoRR, 2008)

Constraint satisfaction problems with isolated solutions are hard - Lenka Zdeborová; Marc Mézard (CoRR, 2008)

Pairs of SAT-assignments in random Boolean formulæ. - Hervé Daudé; Marc Mézard; Thierry Mora; Riccardo Zecchina (Theor. Comput. Sci., 2008)

Susceptibility Propagation for Constraint Satisfaction Problems - Saburo Higuchi; Marc Mézard (CoRR, 2009)

Decimation flows in constraint satisfaction problems - Saburo Higuchi; Marc Mézard (CoRR, 2009)

Statistical physics-based reconstruction in compressed sensing - Florent Krzakala; Marc Mézard; François Sausset; Yifan Sun; Lenka Zdeborová (CoRR, 2011)

Special Section on Constraint Satisfaction Problems and Message Passing Algorithms. - Marc Mézard; Prasad Tetali (SIAM J. Discret. Math., 2011)

Group Testing With Random Pools: Optimal Two-Stage Algorithms. - Marc Mézard; Cristina Toninelli (IEEE Trans. Inf. Theory, 2011)

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

Probabilistic Reconstruction in Compressed Sensing: Algorithms, Phase Diagrams, and Threshold Achieving Matrices - Florent Krzakala; Marc Mézard; François Sausset; Yifan Sun; Lenka Zdeborová (CoRR, 2012)

Belief Propagation Reconstruction for Discrete Tomography - Emmanuelle Gouillart; Florent Krzakala; Marc Mézard; Lenka Zdeborová (CoRR, 2012)

Compressed sensing under matrix uncertainty: Optimum thresholds and robust approximate message passing. - Florent Krzakala; Marc Mézard; Lenka Zdeborová (ICASSP, 2013)

Non-adaptive pooling strategies for detection of rare faulty items. - Pan Zhang; Florent Krzakala; Marc Mézard; Lenka Zdeborová (ICC Workshops, 2013)

Phase diagram and approximate message passing for blind calibration and dictionary learning. - Florent Krzakala; Marc Mézard; Lenka Zdeborová (ISIT, 2013)

Inferring the origin of an epidemy with dynamic message-passing algorithm - Andrey Y. Lokhov; Marc Mézard; Hiroki Ohta; Lenka Zdeborová (CoRR, 2013)

Dynamic message-passing equations for models with unidirectional dynamics. - Andrey Y. Lokhov; Marc Mézard; Lenka Zdeborová (CoRR, 2014)

Reweighted Belief Propagation and Quiet Planting for Random K-SAT. - Florent Krzakala; Marc Mézard; Lenka Zdeborová (J. Satisf. Boolean Model. Comput., 2014)

Phase Transitions and Sample Complexity in Bayes-Optimal Matrix Factorization. - Yoshiyuki Kabashima; Florent Krzakala; Marc Mézard; Ayaka Sakata; Lenka Zdeborová (IEEE Trans. Inf. Theory, 2016)

Multi-layer generalized linear estimation. - Andre Manoel; Florent Krzakala; Marc Mézard; Lenka Zdeborová (ISIT, 2017)

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

Modelling the influence of data structure on learning in neural networks. - Sebastian Goldt; Marc Mézard; Florent Krzakala; Lenka Zdeborová (CoRR, 2019)

Generalisation error in learning with random features and the hidden manifold model. - Federica Gerace; Bruno Loureiro; Florent Krzakala; Marc Mézard; Lenka Zdeborová (ICML, 2020)

The Gaussian equivalence of generative models for learning with two-layer neural networks. - Sebastian Goldt; Galen Reeves; Marc Mézard; Florent Krzakala; Lenka Zdeborová (CoRR, 2020)

Epidemic mitigation by statistical inference from contact tracing data. - Antoine Baker; Indaco Biazzo; Alfredo Braunstein; Giovanni Catania; Luca Dall'Asta; Alessandro Ingrosso; Florent Krzakala; Fabio Mazza; Marc Mézard; Anna Paola Muntoni; Maria Refinetti; Stefano Sarao Mannelli; et al. (CoRR, 2020)

The Gaussian equivalence of generative models for learning with shallow neural networks. - Sebastian Goldt; Bruno Loureiro; Galen Reeves; Florent Krzakala; Marc Mézard; Lenka Zdeborová (MSML, 2021)

Learning curves of generic features maps for realistic datasets with a teacher-student model. - Bruno Loureiro; Cédric Gerbelot; Hugo Cui; Sebastian Goldt; Florent Krzakala; Marc Mézard; Lenka Zdeborová (NeurIPS, 2021)

Capturing the learning curves of generic features maps for realistic data sets with a teacher-student model. - Bruno Loureiro; Cédric Gerbelot; Hugo Cui; Sebastian Goldt; Florent Krzakala; Marc Mézard; Lenka Zdeborová (CoRR, 2021)

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

Matrix factorization with neural networks. - Francesco Camilli; Marc Mézard (CoRR, 2022)

The Exponential Capacity of Dense Associative Memories. - Carlo Lucibello; Marc Mézard (CoRR, 2023)

Sparse Representations, Inference and Learning. - Clarissa Lauditi; Emanuele Troiani; Marc Mézard (CoRR, 2023)

The Decimation Scheme for Symmetric Matrix Factorization. - Francesco Camilli; Marc Mézard (CoRR, 2023)

Eigenvector Dreaming. - Marco Benedetti; Louis Carillo; Enzo Marinari; Marc Mézard (CoRR, 2023)

Dynamical Regimes of Diffusion Models. - Giulio Biroli; Tony Bonnaire; Valentin De Bortoli; Marc Mézard (CoRR, 2024)

Kernel Density Estimators in Large Dimensions. - Giulio Biroli; Marc Mézard (CoRR, 2024)

How transformers learn structured data: insights from hierarchical filtering. - Jerome Garnier-Brun; Marc Mézard; Emanuele Moscato; Luca Saglietti (CoRR, 2024)

Optimizing Noise Schedules of Generative Models in High Dimensionss. - Santiago Aranguri; Giulio Biroli; Marc Mézard; Eric Vanden-Eijnden (CoRR, 2025)

Understanding Classifier-Free Guidance: High-Dimensional Theory and Non-Linear Generalizations. - Krunoslav Lehman Pavasovic; Jakob Verbeek; Giulio Biroli; Marc Mézard (CoRR, 2025)

Why Diffusion Models Don't Memorize: The Role of Implicit Dynamical Regularization in Training. - Tony Bonnaire; Raphaël Urfin; Giulio Biroli; Marc Mézard (CoRR, 2025)