Threshold values, stability analysis and high-q asymptotics for the coloring problem on random graphs - Florent Krzakala; Andrea Pagnani; Martin Weigt (CoRR, 2004)

Phase Transitions in the Coloring of Random Graphs - Lenka Zdeborová; Florent Krzakala (CoRR, 2007)

Constraint optimization and landscapes - Florent Krzakala; Jorge Kurchan (CoRR, 2007)

Phase Transitions and Computational Difficulty in Random Constraint Satisfaction Problems - Florent Krzakala; Lenka Zdeborová (CoRR, 2007)

A Landscape Analysis of Constraint Satisfaction Problems - Florent Krzakala; Jorge Kurchan (CoRR, 2007)

Gibbs states and the set of solutions of random constraint satisfaction problems. - Florent Krzakala; Andrea Montanari; Federico Ricci-Tersenghi; Guilhem Semerjian; Lenka Zdeborová (Proc. Natl. Acad. Sci. USA, 2007)

First-order transitions and the performance of quantum algorithms in random optimization problems. - Thomas Jörg; Florent Krzakala; Guilhem Semerjian; Francesco Zamponi (CoRR, 2009)

Hiding Quiet Solutions in Random Constraint Satisfaction Problems - Florent Krzakala; Lenka Zdeborová (CoRR, 2009)

Quantum energy gaps and first-order mean-field-like transitions - Thomas Jörg; Florent Krzakala; Jorge Kurchan; Anthony C. Maggs; J. Pujos (CoRR, 2009)

Phase transition in the detection of modules in sparse networks - Aurélien Decelle; Florent Krzakala; Cristopher Moore; Lenka Zdeborová (CoRR, 2011)

Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications - Aurélien Decelle; Florent Krzakala; Cristopher Moore; Lenka Zdeborová (CoRR, 2011)

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

Quiet Planting in the Locked Constraint Satisfaction Problems. - Lenka Zdeborová; Florent Krzakala (SIAM J. Discret. Math., 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)

Comparative Study for Inference of Hidden Classes in Stochastic Block Models - Pan Zhang; Florent Krzakala; Jörg Reichardt; Lenka Zdeborová (CoRR, 2012)

Model Selection for Degree-corrected Block Models - Xiaoran Yan; Jacob E. Jensen; Florent Krzakala; Cristopher Moore; Cosma Rohilla Shalizi; Lenka Zdeborová; Pan Zhang; Yaojia Zhu (CoRR, 2012)

The Quantum Adiabatic Algorithm applied to random optimization problems: the quantum spin glass perspective - Victor Bapst; Laura Foini; Florent Krzakala; Guilhem Semerjian; Francesco Zamponi (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)

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

Blind Calibration in Compressed Sensing using Message Passing Algorithms. - Christophe Schülke; Francesco Caltagirone; Florent Krzakala; Lenka Zdeborová (NIPS, 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)

Spectral redemption: clustering sparse networks. - Florent Krzakala; Cristopher Moore; Elchanan Mossel; Joe Neeman; Allan Sly; Lenka Zdeborová; Pan Zhang (CoRR, 2013)

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

On convergence of approximate message passing. - Francesco Caltagirone; Lenka Zdeborová; Florent Krzakala (ISIT, 2014)

Variational free energies for compressed sensing. - Florent Krzakala; Andre Manoel; Eric W. Tramel; Lenka Zdeborová (ISIT, 2014)

Spectral Clustering of graphs with the Bethe Hessian. - Alaa Saade; Florent Krzakala; Lenka Zdeborová (NIPS, 2014)

Sparse Estimation with the Swept Approximated Message-Passing Algorithm. - Andre Manoel; Florent Krzakala; Eric W. Tramel; Lenka Zdeborová (CoRR, 2014)

Spectral density of the non-backtracking operator. - Alaa Saade; Florent Krzakala; 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)

Spectral detection on sparse hypergraphs. - Maria Chiara Angelini; Francesco Caltagirone; Florent Krzakala; Lenka Zdeborová (Allerton, 2015)

MMSE of probabilistic low-rank matrix estimation: Universality with respect to the output channel. - Thibault Lesieur; Florent Krzakala; Lenka Zdeborová (Allerton, 2015)

Phase recovery from a Bayesian point of view: The variational approach. - Angélique Dremeau; Florent Krzakala (ICASSP, 2015)

Adaptive damping and mean removal for the generalized approximate message passing algorithm. - Jeremy P. Vila; Philip Schniter; Sundeep Rangan; Florent Krzakala; Lenka Zdeborová (ICASSP, 2015)

Swept Approximate Message Passing for Sparse Estimation. - Andre Manoel; Florent Krzakala; Eric W. Tramel; Lenka Zdeborová (ICML, 2015)

Phase transitions in sparse PCA. - Thibault Lesieur; Florent Krzakala; Lenka Zdeborová (ISIT, 2015)

Spectral detection in the censored block model. - Alaa Saade; Marc Lelarge; Florent Krzakala; Lenka Zdeborová (ISIT, 2015)

Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy. - Marylou Gabrié; Eric W. Tramel; Florent Krzakala (NIPS, 2015)

Matrix Completion from Fewer Entries: Spectral Detectability and Rank Estimation. - Alaa Saade; Florent Krzakala; Lenka Zdeborová (NIPS, 2015)

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

Training Restricted Boltzmann Machines via the Thouless-Anderson-Palmer Free Energy. - Marylou Gabrié; Eric W. Tramel; Florent Krzakala (CoRR, 2015)

Intensity-only optical compressive imaging using a multiply scattering material : a double phase retrieval system. - Boshra Rajaei; Eric W. Tramel; Sylvain Gigan; Florent Krzakala; Laurent Daudet (CoRR, 2015)

Approximate Message Passing with Restricted Boltzmann Machine Priors. - Eric W. Tramel; Angélique Drémeau; Florent Krzakala (CoRR, 2015)

Statistical physics of inference: Thresholds and algorithms. - Lenka Zdeborová; Florent Krzakala (CoRR, 2015)

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

Phase transitions and optimal algorithms in high-dimensional Gaussian mixture clustering. - Thibault Lesieur; Caterina De Bacco; Jess Banks; Florent Krzakala; Cristopher Moore; Lenka Zdeborová (Allerton, 2016)

Intensity-only optical compressive imaging using a multiply scattering material and a double phase retrieval approach. - Boshra Rajaei; Eric W. Tramel; Sylvain Gigan; Florent Krzakala; Laurent Daudet (ICASSP, 2016)

Random projections through multiple optical scattering: Approximating Kernels at the speed of light. - Alaa Saade; Francesco Caltagirone; Igor Carron; Laurent Daudet; Angélique Dremeau; Sylvain Gigan; Florent Krzakala (ICASSP, 2016)

Clustering from sparse pairwise measurements. - Alaa Saade; Marc Lelarge; Florent Krzakala; Lenka Zdeborová (ISIT, 2016)

Mutual information in rank-one matrix estimation. - Florent Krzakala; Jiaming Xu 002; Lenka Zdeborová (ITW, 2016)

Inferring sparsity: Compressed sensing using generalized restricted Boltzmann machines. - Eric W. Tramel; Andre Manoel; Francesco Caltagirone; Marylou Gabrié; Florent Krzakala (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)

Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16). - Vinayak Abrol; Olivier Absil; Pierre-Antoine Absil; Sandrine Anthoine; Philippe Antoine; Thomas Arildsen; Nancy Bertin; Folkert Bleichrodt; Jérôme Bobin; Anne Bol; Antoine Bonnefoy; Francesco Caltagirone; et al. (CoRR, 2016)

Fast Randomized Semi-Supervised Clustering. - Alaa Saade; Florent Krzakala; Marc Lelarge; Lenka Zdeborová (CoRR, 2016)

Performance Limits for Noisy Multi-Measurement Vector Problems. - Junan Zhu; Dror Baron; Florent Krzakala (CoRR, 2016)

Fast Phase Retrieval for High Dimensions: A Block-Based Approach. - Boshra Rajaei; Sylvain Gigan; Florent Krzakala; Laurent Daudet (IEEE Signal Process. Lett., 2016)

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)

Streaming Bayesian inference: Theoretical limits and mini-batch approximate message-passing. - Andre Manoel; Florent Krzakala; Eric W. Tramel; Lenka Zdeborová (Allerton, 2017)

Statistical and computational phase transitions in spiked tensor estimation. - Thibault Lesieur; Léo Miolane; Marc Lelarge; Florent Krzakala; Lenka Zdeborová (ISIT, 2017)

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

Information-theoretic thresholds from the cavity method. - Amin Coja-Oghlan; Florent Krzakala; Will Perkins 001; Lenka Zdeborová (STOC, 2017)

Constrained Low-rank Matrix Estimation: Phase Transitions, Approximate Message Passing and Applications. - Thibault Lesieur; Florent Krzakala; Lenka Zdeborová (CoRR, 2017)

A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines. - Eric W. Tramel; Marylou Gabrié; Andre Manoel; Francesco Caltagirone; Florent Krzakala (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)

Finite Size Corrections and Likelihood Ratio Fluctuations in the Spiked Wigner Model. - Ahmed El Alaoui; Florent Krzakala; Michael I. Jordan (CoRR, 2017)

Robust Phase Retrieval with the Swept Approximate Message Passing (prSAMP) Algorithm. - Boshra Rajaei; Sylvain Gigan; Florent Krzakala; Laurent Daudet (Image Process. Line, 2017)

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

Performance Limits for Noisy Multimeasurement Vector Problems. - Junan Zhu; Dror Baron; Florent Krzakala (IEEE Trans. Signal Process., 2017)

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

Estimation in the Spiked Wigner Model: A Short Proof of the Replica Formula. - Ahmed El Alaoui; Florent Krzakala (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)

Scaling Up Echo-State Networks With Multiple Light Scattering. - Jonathan Dong; Sylvain Gigan; Florent Krzakala; Gilles Wainrib (SSP, 2018)

Approximate Survey Propagation for Statistical Inference. - Fabrizio Antenucci; Florent Krzakala; Pierfrancesco Urbani; Lenka Zdeborová (CoRR, 2018)

Approximate message-passing for convex optimization with non-separable penalties. - Andre Manoel; Florent Krzakala; Gaël Varoquaux; Bertrand Thirion; Lenka Zdeborová (CoRR, 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)

Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference. - Stefano Sarao Mannelli; Giulio Biroli; Chiara Cammarota; Florent Krzakala; Pierfrancesco Urbani; Lenka Zdeborová (CoRR, 2018)

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

Spectral Method for Multiplexed Phase Retrieval and Application in Optical Imaging in Complex Media. - Jonathan Dong; Florent Krzakala; Sylvain Gigan (ICASSP, 2019)

Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models. - Stefano Sarao Mannelli; Florent Krzakala; Pierfrancesco Urbani; Lenka Zdeborová (ICML, 2019)

Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup. - Sebastian Goldt; Madhu Advani; Andrew M. Saxe; Florent Krzakala; Lenka Zdeborová (NeurIPS, 2019)

Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models. - Stefano Sarao Mannelli; Giulio Biroli; Chiara Cammarota; Florent Krzakala; Lenka Zdeborová (NeurIPS, 2019)

Generalisation dynamics of online learning in over-parameterised neural networks. - Sebastian Goldt; Madhu S. Advani; Andrew M. Saxe; Florent Krzakala; Lenka Zdeborová (CoRR, 2019)

Passed & Spurious: analysing descent algorithms and local minima in spiked matrix-tensor model. - Stefano Sarao Mannelli; Florent Krzakala; Pierfrancesco Urbani; Lenka Zdeborová (CoRR, 2019)

Principled Training of Neural Networks with Direct Feedback Alignment. - Julien Launay; Iacopo Poli; Florent Krzakala (CoRR, 2019)

On the Universality of Noiseless Linear Estimation with Respect to the Measurement Matrix. - Alia Abbara; Antoine Baker; Florent Krzakala; Lenka Zdeborová (CoRR, 2019)

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

Optical Reservoir Computing using multiple light scattering for chaotic systems prediction. - Jonathan Dong; Mushegh Rafayelyan; Florent Krzakala; Sylvain Gigan (CoRR, 2019)

Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model. - Stefano Sarao Mannelli; Giulio Biroli; Chiara Cammarota; Florent Krzakala; 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)

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

Decoding from Pooled Data: Sharp Information-Theoretic Bounds. - Ahmed El Alaoui; Aaditya Ramdas; Florent Krzakala; Lenka Zdeborová; Michael I. Jordan (SIAM J. Math. Data Sci., 2019)

Decoding From Pooled Data: Phase Transitions of Message Passing. - Ahmed El Alaoui; Aaditya Ramdas; Florent Krzakala; Lenka Zdeborová; Michael I. Jordan (IEEE Trans. Inf. Theory, 2019)

Asymptotic Errors for High-Dimensional Convex Penalized Linear Regression beyond Gaussian Matrices. - Cédric Gerbelot; Alia Abbara; Florent Krzakala (COLT, 2020)

Kernel Computations from Large-Scale Random Features Obtained by Optical Processing Units. - Ruben Ohana; Jonas Wacker; Jonathan Dong; Sébastien Marmin; Florent Krzakala; Maurizio Filippone; Laurent Daudet (ICASSP, 2020)

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 Role of Regularization in Classification of High-dimensional Noisy Gaussian Mixture. - Francesca Mignacco; Florent Krzakala; Yue M. Lu; Pierfrancesco Urbani; Lenka Zdeborová (ICML, 2020)

Double Trouble in Double Descent: Bias and Variance(s) in the Lazy Regime. - Stéphane d'Ascoli; Maria Refinetti; Giulio Biroli; Florent Krzakala (ICML, 2020)

Rademacher complexity and spin glasses: A link between the replica and statistical theories of learning. - Alia Abbara; Benjamin Aubin; Florent Krzakala; Lenka Zdeborová (MSML, 2020)

Exact asymptotics for phase retrieval and compressed sensing with random generative priors. - Benjamin Aubin; Bruno Loureiro; Antoine Baker; Florent Krzakala; Lenka Zdeborová (MSML, 2020)

Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization. - Benjamin Aubin; Florent Krzakala; Yue M. Lu; Lenka Zdeborová (NeurIPS, 2020)

Reservoir Computing meets Recurrent Kernels and Structured Transforms. - Jonathan Dong; Ruben Ohana; Mushegh Rafayelyan; Florent Krzakala (NeurIPS, 2020)

Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures. - Julien Launay; Iacopo Poli; François Boniface; Florent Krzakala (NeurIPS, 2020)

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

Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval. - Stefano Sarao Mannelli; Giulio Biroli; Chiara Cammarota; Florent Krzakala; Pierfrancesco Urbani; Lenka Zdeborová (NeurIPS, 2020)

Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification. - Francesca Mignacco; Florent Krzakala; Pierfrancesco Urbani; Lenka Zdeborová (NeurIPS, 2020)

Large-Scale Optical Reservoir Computing for Spatiotemporal Chaotic Systems Prediction. - Mushegh Rafayelyan; Jonathan Dong; Yongqi Tan; Florent Krzakala; Sylvain Gigan (CoRR, 2020)

The role of regularization in classification of high-dimensional noisy Gaussian mixture. - Francesca Mignacco; Florent Krzakala; Yue M. Lu; Lenka Zdeborová (CoRR, 2020)

TRAMP: Compositional Inference with TRee Approximate Message Passing. - Antoine Baker; Benjamin Aubin; Florent Krzakala; Lenka Zdeborová (CoRR, 2020)

Light-in-the-loop: using a photonics co-processor for scalable training of neural networks. - Julien Launay; Iacopo Poli; Kilian Müller; Igor Carron; Laurent Daudet; Florent Krzakala; Sylvain Gigan (CoRR, 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)

Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignment. - Julien Launay; Iacopo Poli; Kilian Müller; Gustave Pariente; Igor Carron; Laurent Daudet; Florent Krzakala; Sylvain Gigan (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)

LightOn Optical Processing Unit : Scaling-up AI and HPC with a Non von Neumann co-processor. - Charles Brossollet; Alessandro Cappelli; Igor Carron; Charidimos Chaintoutis; Amélie Chatelain; Laurent Daudet; Sylvain Gigan; Daniel Hesslow; Florent Krzakala; Julien Launay; Safa Mokaadi; Fabien Moreau; et al. (HCS, 2021)

Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed. - Maria Refinetti; Sebastian Goldt; Florent Krzakala; Lenka Zdeborová (ICML, 2021)

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)

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

Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime. - Hugo Cui; Bruno Loureiro; Florent Krzakala; Lenka Zdeborová (NeurIPS, 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)

Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions. - Bruno Loureiro; Gabriele Sicuro; Cédric Gerbelot; Alessandro Pacco; Florent Krzakala; 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)

Learning Gaussian Mixtures with Generalised Linear Models: Precise Asymptotics in High-dimensions. - Bruno Loureiro; Gabriele Sicuro; Cédric Gerbelot; Alessandro Pacco; Florent Krzakala; 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)

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

Adversarial Robustness by Design Through Analog Computing And Synthetic Gradients. - Alessandro Cappelli; Ruben Ohana; Julien Launay; Laurent Meunier; Iacopo Poli; Florent Krzakala (ICASSP, 2022)

Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension. - Bruno Loureiro; Cédric Gerbelot; Maria Refinetti; Gabriele Sicuro; Florent Krzakala (ICML, 2022)

Secure Coding via Gaussian Random Fields. - Ali Bereyhi; Bruno Loureiro; Florent Krzakala; Ralf R. Müller; Hermann Schulz-Baldes (ISIT, 2022)

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

Multi-layer State Evolution Under Random Convolutional Design. - Max Daniels; Cédric Gerbelot; Florent Krzakala; Lenka Zdeborová (NeurIPS, 2022)

Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap. - Luca Pesce; Bruno Loureiro; Florent Krzakala; Lenka Zdeborová (NeurIPS, 2022)

Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks. - Rodrigo Veiga 001; Ludovic Stephan; Bruno Loureiro; Florent Krzakala; Lenka Zdeborová (NeurIPS, 2022)

Error Rates for Kernel Classification under Source and Capacity Conditions. - Hugo Cui; Bruno Loureiro; Florent Krzakala; Lenka Zdeborová (CoRR, 2022)

Theoretical characterization of uncertainty in high-dimensional linear classification. - Lucas Clarté; Bruno Loureiro; Florent Krzakala; Lenka Zdeborová (CoRR, 2022)

Gaussian Universality of Linear Classifiers with Random Labels in High-Dimension. - Federica Gerace; Florent Krzakala; Bruno Loureiro; Ludovic Stephan; Lenka Zdeborová (CoRR, 2022)

A study of uncertainty quantification in overparametrized high-dimensional models. - Lucas Clarté; Bruno Loureiro; Florent Krzakala; Lenka Zdeborová (CoRR, 2022)

On double-descent in uncertainty quantification in overparametrized models. - Lucas Clarté; Bruno Loureiro; Florent Krzakala; Lenka Zdeborová (AISTATS, 2023)

From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks. - Luca Arnaboldi 002; Ludovic Stephan; Florent Krzakala; Bruno Loureiro (COLT, 2023)

Bayes-optimal Learning of Deep Random Networks of Extensive-width. - Hugo Cui; Florent Krzakala; Lenka Zdeborová (ICML, 2023)

Are Gaussian Data All You Need? The Extents and Limits of Universality in High-Dimensional Generalized Linear Estimation. - Luca Pesce; Florent Krzakala; Bruno Loureiro; Ludovic Stephan (ICML, 2023)

Compressed sensing with ℓ0-norm: statistical physics analysis & algorithms for signal recovery. - Damien Barbier; Carlo Lucibello; Luca Saglietti; Florent Krzakala; Lenka Zdeborová (ITW, 2023)

Universality laws for Gaussian mixtures in generalized linear models. - Yatin Dandi; Ludovic Stephan; Florent Krzakala; Bruno Loureiro; Lenka Zdeborová (NeurIPS, 2023)

Optimal Algorithms for the Inhomogeneous Spiked Wigner Model. - Aleksandr Pak; Justin Ko; Florent Krzakala (NeurIPS, 2023)

Expectation consistency for calibration of neural networks. - Lucas Clarté; Bruno Loureiro; Florent Krzakala; Lenka Zdeborová (UAI, 2023)

Optimal Learning of Deep Random Networks of Extensive-width. - Hugo Cui; Florent Krzakala; Lenka Zdeborová (CoRR, 2023)

Statistical mechanics of the maximum-average submatrix problem. - Vittorio Erba; Florent Krzakala; Rodrigo Pérez; Lenka Zdeborová (CoRR, 2023)

Compressed sensing with l0-norm: statistical physics analysis and algorithms for signal recovery. - Damien Barbier; Carlo Lucibello; Luca Saglietti; Florent Krzakala; Lenka Zdeborová (CoRR, 2023)

Learning Two-Layer Neural Networks, One (Giant) Step at a Time. - Yatin Dandi; Florent Krzakala; Bruno Loureiro; Luca Pesce; Ludovic Stephan (CoRR, 2023)

Escaping mediocrity: how two-layer networks learn hard single-index models with SGD. - Luca Arnaboldi 002; Florent Krzakala; Bruno Loureiro; Ludovic Stephan (CoRR, 2023)

Asymptotic Characterisation of Robust Empirical Risk Minimisation Performance in the Presence of Outliers. - Matteo Vilucchio; Emanuele Troiani; Vittorio Erba; Florent Krzakala (CoRR, 2023)

Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective. - Davide Ghio; Yatin Dandi; Florent Krzakala; Lenka Zdeborová (CoRR, 2023)

Tree-AMP: Compositional Inference with Tree Approximate Message Passing. - Antoine Baker; Florent Krzakala; Benjamin Aubin; Lenka Zdeborová (J. Mach. Learn. Res., 2023)

Bayesian reconstruction of memories stored in neural networks from their connectivity. - Sebastian Goldt; Florent Krzakala; Lenka Zdeborová; Nicolas Brunel (PLoS Comput. Biol., 2023)

Asymptotic Errors for Teacher-Student Convex Generalized Linear Models (Or: How to Prove Kabashima's Replica Formula). - Cédric Gerbelot; Alia Abbara; Florent Krzakala (IEEE Trans. Inf. Theory, 2023)

Error scaling laws for kernel classification under source and capacity conditions. - Hugo Cui; Bruno Loureiro; Florent Krzakala; Lenka Zdeborová (Mach. Learn. Sci. Technol., 2023)

Bayesian Inference With Nonlinear Generative Models: Comments on Secure Learning. - Ali Bereyhi; Bruno Loureiro; Florent Krzakala; Ralf R. Müller; Hermann Schulz-Baldes (IEEE Trans. Inf. Theory, 2023)

Asymptotic Characterisation of the Performance of Robust Linear Regression in the Presence of Outliers. - Matteo Vilucchio; Emanuele Troiani; Vittorio Erba; Florent Krzakala (AISTATS, 2024)

Fundamental Limits of Non-Linear Low-Rank Matrix Estimation. - Pierre Mergny; Justin Ko; Florent Krzakala; Lenka Zdeborová (COLT, 2024)

Analysis of Learning a Flow-based Generative Model from Limited Sample Complexity. - Hugo Cui; Florent Krzakala; Eric Vanden-Eijnden; Lenka Zdeborová (ICLR, 2024)

Online Learning and Information Exponents: The Importance of Batch size & Time/Complexity Tradeoffs. - Luca Arnaboldi 002; Yatin Dandi; Florent Krzakala; Bruno Loureiro; Luca Pesce; Ludovic Stephan (ICML, 2024)

Asymptotics of feature learning in two-layer networks after one gradient-step. - Hugo Cui; Luca Pesce; Yatin Dandi; Florent Krzakala; Yue M. Lu; Lenka Zdeborová; Bruno Loureiro (ICML, 2024)

The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents. - Yatin Dandi; Emanuele Troiani; Luca Arnaboldi 002; Luca Pesce; Lenka Zdeborová; Florent Krzakala (ICML, 2024)

Spectral Phase Transition and Optimal PCA in Block-Structured Spiked Models. - Pierre Mergny; Justin Ko; Florent Krzakala (ICML, 2024)

A Phase Transition between Positional and Semantic Learning in a Solvable Model of Dot-Product Attention. - Hugo Cui; Freya Behrens; Florent Krzakala; Lenka Zdeborová (NeurIPS, 2024)

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)

Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression. - Lucas Clarté; Adrien Vandenbroucque; Guillaume Dalle; Bruno Loureiro; Florent Krzakala; Lenka Zdeborová (UAI, 2024)

A High Dimensional Model for Adversarial Training: Geometry and Trade-Offs. - Kasimir Tanner; Matteo Vilucchio; Bruno Loureiro; Florent Krzakala (CoRR, 2024)

Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions. - Luca Arnaboldi 002; Yatin Dandi; Florent Krzakala; Luca Pesce; Ludovic Stephan (CoRR, 2024)

Fundamental limits of weak learnability in high-dimensional multi-index models. - Emanuele Troiani; Yatin Dandi; Leonardo Defilippis; Lenka Zdeborová; Bruno Loureiro; Florent Krzakala (CoRR, 2024)

Online Learning and Information Exponents: On The Importance of Batch size, and Time/Complexity Tradeoffs. - Luca Arnaboldi 002; Yatin Dandi; Florent Krzakala; Bruno Loureiro; Luca Pesce; Ludovic Stephan (CoRR, 2024)

The phase diagram of compressed sensing with ℓ0-norm regularization. - Damien Barbier; Carlo Lucibello; Luca Saglietti; Florent Krzakala; Lenka Zdeborová (CoRR, 2024)

Optical training of large-scale Transformers and deep neural networks with direct feedback alignment. - Ziao Wang; Kilian Müller; Matthew J. Filipovich; Julien Launay; Ruben Ohana; Gustave Pariente; Safa Mokaadi; Charles Brossollet; Fabien Moreau; Alessandro Cappelli; Iacopo Poli; Igor Carron; et al. (CoRR, 2024)

Rigorous Dynamical Mean-Field Theory for Stochastic Gradient Descent Methods. - Cédric Gerbelot; Emanuele Troiani; Francesca Mignacco; Florent Krzakala; Lenka Zdeborová (SIAM J. Math. Data Sci., 2024)

A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities. - Yatin Dandi; Luca Pesce; Hugo Cui; Florent Krzakala; Yue M. Lu; Bruno Loureiro (AISTATS, 2025)

A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs. - Kasimir Tanner; Matteo Vilucchio; Bruno Loureiro; Florent Krzakala (AISTATS, 2025)

Fundamental computational limits of weak learnability in high-dimensional multi-index models. - Emanuele Troiani; Yatin Dandi; Leonardo Defilippis; Lenka Zdeborová; Bruno Loureiro; Florent Krzakala (AISTATS, 2025)

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

Fundamental limits of learning in sequence multi-index models and deep attention networks: High-dimensional asymptotics and sharp thresholds. - Emanuele Troiani; Hugo Cui; Yatin Dandi; Florent Krzakala; Lenka Zdeborová (CoRR, 2025)

Optimal Spectral Transitions in High-Dimensional Multi-Index Models. - Leonardo Defilippis; Yatin Dandi; Pierre Mergny; Florent Krzakala; Bruno Loureiro (CoRR, 2025)

The Computational Advantage of Depth: Learning High-Dimensional Hierarchical Functions with Gradient Descent. - Yatin Dandi; Luca Pesce; Lenka Zdeborová; Florent Krzakala (CoRR, 2025)

Asymptotics of Non-Convex Generalized Linear Models in High-Dimensions: A proof of the replica formula. - Matteo Vilucchio; Yatin Dandi; Cédric Gerbelot; Florent Krzakala (CoRR, 2025)

The Nuclear Route: Sharp Asymptotics of ERM in Overparameterized Quadratic Networks. - Vittorio Erba; Emanuele Troiani; Lenka Zdeborová; Florent Krzakala (CoRR, 2025)

Learning with Restricted Boltzmann Machines: Asymptotics of AMP and GD in High Dimensions. - Yizhou Xu; Florent Krzakala; Lenka Zdeborová (CoRR, 2025)

Asymptotics of SGD in Sequence-Single Index Models and Single-Layer Attention Networks. - Luca Arnaboldi 002; Bruno Loureiro; Ludovic Stephan; Florent Krzakala; Lenka Zdeborová (CoRR, 2025)

Computational Thresholds in Multi-Modal Learning via the Spiked Matrix-Tensor Model. - Hugo Tabanelli; Pierre Mergny; Lenka Zdeborová; Florent Krzakala (CoRR, 2025)