Florent Krzakala

285 papers A* 42A 7B 17Misc 8Journal 191Unranked 20

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Noise Sensitivity Exponent Controls Large Statistical-to-Computational Gaps in Single- and Multi-Index Models. CoRR Leonardo Defilippis, Florent Krzakala, Bruno Loureiro, Antoine Maillard
2026	J	`jnl`	ColBERT-Zero: To Pre-train Or Not To Pre-train ColBERT models. CoRR Antoine Chaffin, Luca Arnaboldi, Amélie Chatelain, Florent Krzakala
2026	J	`jnl`	Deep Learning of Compositional Targets with Hierarchical Spectral Methods. CoRR Hugo Tabanelli, Yatin Dandi, Luca Pesce, Florent Krzakala
2026	J	`jnl`	Optimal scaling laws in learning hierarchical multi-index models. CoRR Leonardo Defilippis, Florent Krzakala, Bruno Loureiro, Antoine Maillard
2026	J	`jnl`	Provable Learning of Random Hierarchy Models and Hierarchical Shallow-to-Deep Chaining. CoRR Yunwei Ren, Yatin Dandi, Florent Krzakala, Jason D. Lee
2025	A	`conf`	A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs. AISTATS Kasimir Tanner, Matteo Vilucchio, Bruno Loureiro, Florent Krzakala
2025	A	`conf`	A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities. AISTATS Yatin Dandi, Luca Pesce, Hugo Cui, Florent Krzakala, Yue M. Lu, Bruno Loureiro
2025	J	`jnl`	Asymptotics of Non-Convex Generalized Linear Models in High-Dimensions: A proof of the replica formula. CoRR Matteo Vilucchio, Yatin Dandi, Cédric Gerbelot, Florent Krzakala
2025	J	`jnl`	Asymptotics of SGD in Sequence-Single Index Models and Single-Layer Attention Networks. CoRR Luca Arnaboldi, Bruno Loureiro, Ludovic Stephan, Florent Krzakala, Lenka Zdeborová
2025	J	`jnl`	Computational Thresholds in Multi-Modal Learning via the Spiked Matrix-Tensor Model. CoRR Hugo Tabanelli, Pierre Mergny, Lenka Zdeborová, Florent Krzakala
2025	A*	`conf`	Fundamental Limits of Matrix Sensing: Exact Asymptotics, Universality, and Applications. COLT Yizhou Xu, Antoine Maillard, Lenka Zdeborová, Florent Krzakala
2025	J	`jnl`	Fundamental Limits of Matrix Sensing: Exact Asymptotics, Universality, and Applications. CoRR Yizhou Xu, Antoine Maillard, Lenka Zdeborová, Florent Krzakala
2025	A	`conf`	Fundamental computational limits of weak learnability in high-dimensional multi-index models. AISTATS Emanuele Troiani, Yatin Dandi, Leonardo Defilippis, Lenka Zdeborová, Bruno Loureiro, Florent Krzakala
2025	J	`jnl`	Fundamental limits of learning in sequence multi-index models and deep attention networks: High-dimensional asymptotics and sharp thresholds. CoRR Emanuele Troiani, Hugo Cui, Yatin Dandi, Florent Krzakala, Lenka Zdeborová
2025	A*	`conf`	Fundamental limits of learning in sequence multi-index models and deep attention networks: high-dimensional asymptotics and sharp thresholds. ICML Emanuele Troiani, Hugo Cui, Yatin Dandi, Florent Krzakala, Lenka Zdeborová
2025	J	`jnl`	Inductive Bias and Spectral Properties of Single-Head Attention in High Dimensions. CoRR Fabrizio Boncoraglio, Vittorio Erba, Emanuele Troiani, Florent Krzakala, Lenka Zdeborová
2025	J	`jnl`	Learning with Restricted Boltzmann Machines: Asymptotics of AMP and GD in High Dimensions. CoRR Yizhou Xu, Florent Krzakala, Lenka Zdeborová
2025	J	`jnl`	Optimal Spectral Transitions in High-Dimensional Multi-Index Models. CoRR Leonardo Defilippis, Yatin Dandi, Pierre Mergny, Florent Krzakala, Bruno Loureiro
2025	J	`jnl`	Scaling Laws and Spectra of Shallow Neural Networks in the Feature Learning Regime. CoRR Leonardo Defilippis, Yizhou Xu, Julius Girardin, Emanuele Troiani, Vittorio Erba, Lenka Zdeborová, Bruno Loureiro, Florent Krzakala
2025	J	`jnl`	The Computational Advantage of Depth: Learning High-Dimensional Hierarchical Functions with Gradient Descent. CoRR Yatin Dandi, Luca Pesce, Lenka Zdeborová, Florent Krzakala
2025	J	`jnl`	The Nuclear Route: Sharp Asymptotics of ERM in Overparameterized Quadratic Networks. CoRR Vittorio Erba, Emanuele Troiani, Lenka Zdeborová, Florent Krzakala
2024	J	`jnl`	A High Dimensional Model for Adversarial Training: Geometry and Trade-Offs. CoRR Kasimir Tanner, Matteo Vilucchio, Bruno Loureiro, Florent Krzakala
2024	A*	`conf`	A Phase Transition between Positional and Semantic Learning in a Solvable Model of Dot-Product Attention. NeurIPS Hugo Cui, Freya Behrens, Florent Krzakala, Lenka Zdeborová
2024	J	`jnl`	A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities. CoRR Yatin Dandi, Luca Pesce, Hugo Cui, Florent Krzakala, Yue M. Lu, Bruno Loureiro
2024	J	`jnl`	A phase transition between positional and semantic learning in a solvable model of dot-product attention. CoRR Hugo Cui, Freya Behrens, Florent Krzakala, Lenka Zdeborová
2024	A	`conf`	Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression. UAI Lucas Clarté, Adrien Vandenbroucque, Guillaume Dalle, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2024	J	`jnl`	Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression. CoRR Lucas Clarté, Adrien Vandenbroucque, Guillaume Dalle, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2024	A*	`conf`	Analysis of Learning a Flow-based Generative Model from Limited Sample Complexity. ICLR Hugo Cui, Florent Krzakala, Eric Vanden-Eijnden, Lenka Zdeborová
2024	A	`conf`	Asymptotic Characterisation of the Performance of Robust Linear Regression in the Presence of Outliers. AISTATS Matteo Vilucchio, Emanuele Troiani, Vittorio Erba, Florent Krzakala
2024	A*	`conf`	Asymptotics of feature learning in two-layer networks after one gradient-step. ICML Hugo Cui, Luca Pesce, Yatin Dandi, Florent Krzakala, Yue M. Lu, Lenka Zdeborová, Bruno Loureiro
2024	J	`jnl`	Asymptotics of feature learning in two-layer networks after one gradient-step. CoRR Hugo Cui, Luca Pesce, Yatin Dandi, Florent Krzakala, Yue M. Lu, Lenka Zdeborová, Bruno Loureiro
2024	A*	`conf`	Bayes-optimal learning of an extensive-width neural network from quadratically many samples. NeurIPS Antoine Maillard, Emanuele Troiani, Simon Martin, Florent Krzakala, Lenka Zdeborová
2024	J	`jnl`	Bayes-optimal learning of an extensive-width neural network from quadratically many samples. CoRR Antoine Maillard, Emanuele Troiani, Simon Martin, Florent Krzakala, Lenka Zdeborová
2024	A*	`conf`	Fundamental Limits of Non-Linear Low-Rank Matrix Estimation. COLT Pierre Mergny, Justin Ko, Florent Krzakala, Lenka Zdeborová
2024	J	`jnl`	Fundamental limits of Non-Linear Low-Rank Matrix Estimation. CoRR Pierre Mergny, Justin Ko, Florent Krzakala, Lenka Zdeborová
2024	J	`jnl`	Fundamental limits of weak learnability in high-dimensional multi-index models. CoRR Emanuele Troiani, Yatin Dandi, Leonardo Defilippis, Lenka Zdeborová, Bruno Loureiro, Florent Krzakala
2024	J	`jnl`	How Two-Layer Neural Networks Learn, One (Giant) Step at a Time. J. Mach. Learn. Res. Yatin Dandi, Florent Krzakala, Bruno Loureiro, Luca Pesce, Ludovic Stephan
2024	J	`jnl`	Online Learning and Information Exponents: On The Importance of Batch size, and Time/Complexity Tradeoffs. CoRR Luca Arnaboldi, Yatin Dandi, Florent Krzakala, Bruno Loureiro, Luca Pesce, Ludovic Stephan
2024	A*	`conf`	Online Learning and Information Exponents: The Importance of Batch size & Time/Complexity Tradeoffs. ICML Luca Arnaboldi, Yatin Dandi, Florent Krzakala, Bruno Loureiro, Luca Pesce, Ludovic Stephan
2024	J	`jnl`	Optical training of large-scale Transformers and deep neural networks with direct feedback alignment. CoRR 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, Laurent Daudet, Florent Krzakala, Sylvain Gigan
2024	J	`jnl`	Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions. CoRR Luca Arnaboldi, Yatin Dandi, Florent Krzakala, Luca Pesce, Ludovic Stephan
2024	J	`jnl`	Rigorous Dynamical Mean-Field Theory for Stochastic Gradient Descent Methods. SIAM J. Math. Data Sci. Cédric Gerbelot, Emanuele Troiani, Francesca Mignacco, Florent Krzakala, Lenka Zdeborová
2024	A*	`conf`	Spectral Phase Transition and Optimal PCA in Block-Structured Spiked Models. ICML Pierre Mergny, Justin Ko, Florent Krzakala
2024	J	`jnl`	Spectral Phase Transition and Optimal PCA in Block-Structured Spiked models. CoRR Pierre Mergny, Justin Ko, Florent Krzakala
2024	A*	`conf`	The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents. ICML Yatin Dandi, Emanuele Troiani, Luca Arnaboldi, Luca Pesce, Lenka Zdeborová, Florent Krzakala
2024	J	`jnl`	The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents. CoRR Yatin Dandi, Emanuele Troiani, Luca Arnaboldi, Luca Pesce, Lenka Zdeborová, Florent Krzakala
2024	J	`jnl`	The phase diagram of compressed sensing with ℓ CoRR Damien Barbier, Carlo Lucibello, Luca Saglietti, Florent Krzakala, Lenka Zdeborová
2023	J	`jnl`	Analysis of learning a flow-based generative model from limited sample complexity. CoRR Hugo Cui, Florent Krzakala, Eric Vanden-Eijnden, Lenka Zdeborová
2023	A*	`conf`	Are Gaussian Data All You Need? The Extents and Limits of Universality in High-Dimensional Generalized Linear Estimation. ICML Luca Pesce, Florent Krzakala, Bruno Loureiro, Ludovic Stephan
2023	J	`jnl`	Are Gaussian data all you need? Extents and limits of universality in high-dimensional generalized linear estimation. CoRR Luca Pesce, Florent Krzakala, Bruno Loureiro, Ludovic Stephan
2023	J	`jnl`	Asymptotic Characterisation of Robust Empirical Risk Minimisation Performance in the Presence of Outliers. CoRR Matteo Vilucchio, Emanuele Troiani, Vittorio Erba, Florent Krzakala
2023	J	`jnl`	Asymptotic Errors for Teacher-Student Convex Generalized Linear Models (Or: How to Prove Kabashima's Replica Formula). IEEE Trans. Inf. Theory Cédric Gerbelot, Alia Abbara, Florent Krzakala
2023	A*	`conf`	Bayes-optimal Learning of Deep Random Networks of Extensive-width. ICML Hugo Cui, Florent Krzakala, Lenka Zdeborová
2023	J	`jnl`	Bayesian Inference With Nonlinear Generative Models: Comments on Secure Learning. IEEE Trans. Inf. Theory Ali Bereyhi, Bruno Loureiro, Florent Krzakala, Ralf R. Müller, Hermann Schulz-Baldes
2023	J	`jnl`	Bayesian reconstruction of memories stored in neural networks from their connectivity. PLoS Comput. Biol. Sebastian Goldt, Florent Krzakala, Lenka Zdeborová, Nicolas Brunel
2023	J	`jnl`	Compressed sensing with l0-norm: statistical physics analysis and algorithms for signal recovery. CoRR Damien Barbier, Carlo Lucibello, Luca Saglietti, Florent Krzakala, Lenka Zdeborová
2023	B	`conf`	Compressed sensing with ℓ0-norm: statistical physics analysis & algorithms for signal recovery. ITW Damien Barbier, Carlo Lucibello, Luca Saglietti, Florent Krzakala, Lenka Zdeborová
2023	J	`jnl`	Error scaling laws for kernel classification under source and capacity conditions. Mach. Learn. Sci. Technol. Hugo Cui, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2023	J	`jnl`	Escaping mediocrity: how two-layer networks learn hard single-index models with SGD. CoRR Luca Arnaboldi, Florent Krzakala, Bruno Loureiro, Ludovic Stephan
2023	A	`conf`	Expectation consistency for calibration of neural networks. UAI Lucas Clarté, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2023	J	`jnl`	Expectation consistency for calibration of neural networks. CoRR Lucas Clarté, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2023	A*	`conf`	From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks. COLT Luca Arnaboldi, Ludovic Stephan, Florent Krzakala, Bruno Loureiro
2023	J	`jnl`	From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks. CoRR Luca Arnaboldi, Ludovic Stephan, Florent Krzakala, Bruno Loureiro
2023	J	`jnl`	Learning Two-Layer Neural Networks, One (Giant) Step at a Time. CoRR Yatin Dandi, Florent Krzakala, Bruno Loureiro, Luca Pesce, Ludovic Stephan
2023	A	`conf`	On double-descent in uncertainty quantification in overparametrized models. AISTATS Lucas Clarté, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2023	A*	`conf`	Optimal Algorithms for the Inhomogeneous Spiked Wigner Model. NeurIPS Aleksandr Pak, Justin Ko, Florent Krzakala
2023	J	`jnl`	Optimal Algorithms for the Inhomogeneous Spiked Wigner Model. CoRR Aleksandr Pak, Justin Ko, Florent Krzakala
2023	J	`jnl`	Optimal Learning of Deep Random Networks of Extensive-width. CoRR Hugo Cui, Florent Krzakala, Lenka Zdeborová
2023	J	`jnl`	Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective. CoRR Davide Ghio, Yatin Dandi, Florent Krzakala, Lenka Zdeborová
2023	J	`jnl`	Statistical mechanics of the maximum-average submatrix problem. CoRR Vittorio Erba, Florent Krzakala, Rodrigo Pérez, Lenka Zdeborová
2023	J	`jnl`	Theoretical characterization of uncertainty in high-dimensional linear classification. Mach. Learn. Sci. Technol. Lucas Clarté, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2023	J	`jnl`	Tree-AMP: Compositional Inference with Tree Approximate Message Passing. J. Mach. Learn. Res. Antoine Baker, Florent Krzakala, Benjamin Aubin, Lenka Zdeborová
2023	A*	`conf`	Universality laws for Gaussian mixtures in generalized linear models. NeurIPS Yatin Dandi, Ludovic Stephan, Florent Krzakala, Bruno Loureiro, Lenka Zdeborová
2022	J	`jnl`	A study of uncertainty quantification in overparametrized high-dimensional models. CoRR Lucas Clarté, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2022	Misc	`conf`	Adversarial Robustness by Design Through Analog Computing And Synthetic Gradients. ICASSP Alessandro Cappelli, Ruben Ohana, Julien Launay, Laurent Meunier, Iacopo Poli, Florent Krzakala
2022	J	`jnl`	Bayesian Inference with Nonlinear Generative Models: Comments on Secure Learning. CoRR Ali Bereyhi, Bruno Loureiro, Florent Krzakala, Ralf R. Müller, Hermann Schulz-Baldes
2022	J	`jnl`	Error Rates for Kernel Classification under Source and Capacity Conditions. CoRR Hugo Cui, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2022	A*	`conf`	Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension. ICML Bruno Loureiro, Cédric Gerbelot, Maria Refinetti, Gabriele Sicuro, Florent Krzakala
2022	J	`jnl`	Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension. CoRR Bruno Loureiro, Cédric Gerbelot, Maria Refinetti, Gabriele Sicuro, Florent Krzakala
2022	J	`jnl`	Gaussian Universality of Linear Classifiers with Random Labels in High-Dimension. CoRR Federica Gerace, Florent Krzakala, Bruno Loureiro, Ludovic Stephan, Lenka Zdeborová
2022	A*	`conf`	Multi-layer State Evolution Under Random Convolutional Design. NeurIPS Max Daniels, Cédric Gerbelot, Florent Krzakala, Lenka Zdeborová
2022	J	`jnl`	Multi-layer State Evolution Under Random Convolutional Design. CoRR Max Daniels, Cédric Gerbelot, Florent Krzakala, Lenka Zdeborová
2022	—	`conf`	Optimal denoising of rotationally invariant rectangular matrices. MSML Emanuele Troiani, Vittorio Erba, Florent Krzakala, Antoine Maillard, Lenka Zdeborová
2022	J	`jnl`	Optimal denoising of rotationally invariant rectangular matrices. CoRR Emanuele Troiani, Vittorio Erba, Florent Krzakala, Antoine Maillard, Lenka Zdeborová
2022	A*	`conf`	Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks. NeurIPS Rodrigo Veiga, Ludovic Stephan, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2022	J	`jnl`	Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks. CoRR Rodrigo Veiga, Ludovic Stephan, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2022	J	`jnl`	Rigorous dynamical mean field theory for stochastic gradient descent methods. CoRR Cédric Gerbelot, Emanuele Troiani, Francesca Mignacco, Florent Krzakala, Lenka Zdeborová
2022	B	`conf`	Secure Coding via Gaussian Random Fields. ISIT Ali Bereyhi, Bruno Loureiro, Florent Krzakala, Ralf R. Müller, Hermann Schulz-Baldes
2022	J	`jnl`	Secure Coding via Gaussian Random Fields. CoRR Ali Bereyhi, Bruno Loureiro, Florent Krzakala, Ralf R. Müller, Hermann Schulz-Baldes
2022	A*	`conf`	Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap. NeurIPS Luca Pesce, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2022	J	`jnl`	Subspace clustering in high-dimensions: Phase transitions \& Statistical-to-Computational gap. CoRR Luca Pesce, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2022	J	`jnl`	Theoretical characterization of uncertainty in high-dimensional linear classification. CoRR Lucas Clarté, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2021	J	`jnl`	Adversarial Robustness by Design through Analog Computing and Synthetic Gradients. CoRR Alessandro Cappelli, Ruben Ohana, Julien Launay, Laurent Meunier, Iacopo Poli, Florent Krzakala
2021	J	`jnl`	Capturing the learning curves of generic features maps for realistic data sets with a teacher-student model. CoRR Bruno Loureiro, Cédric Gerbelot, Hugo Cui, Sebastian Goldt, Florent Krzakala, Marc Mézard, Lenka Zdeborová
2021	A*	`conf`	Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed. ICML Maria Refinetti, Sebastian Goldt, Florent Krzakala, Lenka Zdeborová
2021	J	`jnl`	Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed. CoRR Maria Refinetti, Sebastian Goldt, Florent Krzakala, Lenka Zdeborová
2021	—	`conf`	Construction of optimal spectral methods in phase retrieval. MSML Antoine Maillard, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
2021	A*	`conf`	Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime. NeurIPS Hugo Cui, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2021	J	`jnl`	Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime. CoRR Hugo Cui, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2021	J	`jnl`	Learning Gaussian Mixtures with Generalised Linear Models: Precise Asymptotics in High-dimensions. CoRR Bruno Loureiro, Gabriele Sicuro, Cédric Gerbelot, Alessandro Pacco, Florent Krzakala, Lenka Zdeborová
2021	A*	`conf`	Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions. NeurIPS Bruno Loureiro, Gabriele Sicuro, Cédric Gerbelot, Alessandro Pacco, Florent Krzakala, Lenka Zdeborová
2021	A*	`conf`	Learning curves of generic features maps for realistic datasets with a teacher-student model. NeurIPS Bruno Loureiro, Cédric Gerbelot, Hugo Cui, Sebastian Goldt, Florent Krzakala, Marc Mézard, Lenka Zdeborová
2021	—	`conf`	LightOn Optical Processing Unit : Scaling-up AI and HPC with a Non von Neumann co-processor. HCS Charles Brossollet, Alessandro Cappelli, Igor Carron, Charidimos Chaintoutis, Amélie Chatelain, Laurent Daudet, Sylvain Gigan, Daniel Hesslow, Florent Krzakala, Julien Launay, Safa Mokaadi, Fabien Moreau, Kilian Müller, Ruben Ohana, Gustave Pariente, Iacopo Poli, Giuseppe Luca Tommasone
2021	J	`jnl`	LightOn Optical Processing Unit: Scaling-up AI and HPC with a Non von Neumann co-processor. CoRR Charles Brossollet, Alessandro Cappelli, Igor Carron, Charidimos Chaintoutis, Amélie Chatelain, Laurent Daudet, Sylvain Gigan, Daniel Hesslow, Florent Krzakala, Julien Launay, Safa Mokaadi, Fabien Moreau, Kilian Müller, Ruben Ohana, Gustave Pariente, Iacopo Poli, Giuseppe Luca Tommasone
2021	J	`jnl`	Perturbative construction of mean-field equations in extensive-rank matrix factorization and denoising. CoRR Antoine Maillard, Florent Krzakala, Marc Mézard, Lenka Zdeborová
2021	—	`conf`	The Gaussian equivalence of generative models for learning with shallow neural networks. MSML Sebastian Goldt, Bruno Loureiro, Galen Reeves, Florent Krzakala, Marc Mézard, Lenka Zdeborová
2021	J	`jnl`	The Spiked Matrix Model With Generative Priors. IEEE Trans. Inf. Theory Benjamin Aubin, Bruno Loureiro, Antoine Maillard, Florent Krzakala, Lenka Zdeborová
2020	A*	`conf`	Asymptotic Errors for High-Dimensional Convex Penalized Linear Regression beyond Gaussian Matrices. COLT Cédric Gerbelot, Alia Abbara, Florent Krzakala
2020	J	`jnl`	Asymptotic Errors for Teacher-Student Convex Generalized Linear Models (or : How to Prove Kabashima's Replica Formula). CoRR Cédric Gerbelot, Alia Abbara, Florent Krzakala
2020	A*	`conf`	Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval. NeurIPS Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová
2020	J	`jnl`	Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval. CoRR Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová
2020	J	`jnl`	Construction of optimal spectral methods in phase retrieval. CoRR Antoine Maillard, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
2020	A*	`conf`	Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures. NeurIPS Julien Launay, Iacopo Poli, François Boniface, Florent Krzakala
2020	J	`jnl`	Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures. CoRR Julien Launay, Iacopo Poli, François Boniface, Florent Krzakala
2020	J	`jnl`	Double Trouble in Double Descent : Bias and Variance(s) in the Lazy Regime. CoRR Stéphane d'Ascoli, Maria Refinetti, Giulio Biroli, Florent Krzakala
2020	A*	`conf`	Double Trouble in Double Descent: Bias and Variance(s) in the Lazy Regime. ICML Stéphane d'Ascoli, Maria Refinetti, Giulio Biroli, Florent Krzakala
2020	A*	`conf`	Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification. NeurIPS Francesca Mignacco, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová
2020	J	`jnl`	Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification. CoRR Francesca Mignacco, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová
2020	J	`jnl`	Epidemic mitigation by statistical inference from contact tracing data. CoRR 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, Lenka Zdeborová
2020	—	`conf`	Exact asymptotics for phase retrieval and compressed sensing with random generative priors. MSML Benjamin Aubin, Bruno Loureiro, Antoine Baker, Florent Krzakala, Lenka Zdeborová
2020	A*	`conf`	Generalisation error in learning with random features and the hidden manifold model. ICML Federica Gerace, Bruno Loureiro, Florent Krzakala, Marc Mézard, Lenka Zdeborová
2020	J	`jnl`	Generalisation error in learning with random features and the hidden manifold model. CoRR Federica Gerace, Bruno Loureiro, Florent Krzakala, Marc Mézard, Lenka Zdeborová
2020	A*	`conf`	Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization. NeurIPS Benjamin Aubin, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
2020	J	`jnl`	Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization. CoRR Benjamin Aubin, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
2020	J	`jnl`	Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignment. CoRR Julien Launay, Iacopo Poli, Kilian Müller, Gustave Pariente, Igor Carron, Laurent Daudet, Florent Krzakala, Sylvain Gigan
2020	Misc	`conf`	Kernel Computations from Large-Scale Random Features Obtained by Optical Processing Units. ICASSP Ruben Ohana, Jonas Wacker, Jonathan Dong, Sébastien Marmin, Florent Krzakala, Maurizio Filippone, Laurent Daudet
2020	J	`jnl`	Large-Scale Optical Reservoir Computing for Spatiotemporal Chaotic Systems Prediction. CoRR Mushegh Rafayelyan, Jonathan Dong, Yongqi Tan, Florent Krzakala, Sylvain Gigan
2020	J	`jnl`	Light-in-the-loop: using a photonics co-processor for scalable training of neural networks. CoRR Julien Launay, Iacopo Poli, Kilian Müller, Igor Carron, Laurent Daudet, Florent Krzakala, Sylvain Gigan
2020	J	`jnl`	Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation. IEEE Trans. Inf. Theory Jean Barbier, Nicolas Macris, Mohamad Dia, Florent Krzakala
2020	A*	`conf`	Phase retrieval in high dimensions: Statistical and computational phase transitions. NeurIPS Antoine Maillard, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2020	J	`jnl`	Phase retrieval in high dimensions: Statistical and computational phase transitions. CoRR Antoine Maillard, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová
2020	—	`conf`	Rademacher complexity and spin glasses: A link between the replica and statistical theories of learning. MSML Alia Abbara, Benjamin Aubin, Florent Krzakala, Lenka Zdeborová
2020	A*	`conf`	Reservoir Computing meets Recurrent Kernels and Structured Transforms. NeurIPS Jonathan Dong, Ruben Ohana, Mushegh Rafayelyan, Florent Krzakala
2020	J	`jnl`	Reservoir Computing meets Recurrent Kernels and Structured Transforms. CoRR Jonathan Dong, Ruben Ohana, Mushegh Rafayelyan, Florent Krzakala
2020	J	`jnl`	TRAMP: Compositional Inference with TRee Approximate Message Passing. CoRR Antoine Baker, Benjamin Aubin, Florent Krzakala, Lenka Zdeborová
2020	J	`jnl`	The Gaussian equivalence of generative models for learning with two-layer neural networks. CoRR Sebastian Goldt, Galen Reeves, Marc Mézard, Florent Krzakala, Lenka Zdeborová
2020	A*	`conf`	The Role of Regularization in Classification of High-dimensional Noisy Gaussian Mixture. ICML Francesca Mignacco, Florent Krzakala, Yue M. Lu, Pierfrancesco Urbani, Lenka Zdeborová
2020	J	`jnl`	The role of regularization in classification of high-dimensional noisy Gaussian mixture. CoRR Francesca Mignacco, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
2019	—	`conf`	Blind Calibration for Sparse Regression: A State Evolution Analysis. CAMSAP Marylou Gabrié, Jean Barbier, Florent Krzakala, Lenka Zdeborová
2019	J	`jnl`	Blind calibration for compressed sensing: State evolution and an online algorithm. CoRR Marylou Gabrié, Jean Barbier, Florent Krzakala, Lenka Zdeborová
2019	J	`jnl`	Decoding From Pooled Data: Phase Transitions of Message Passing. IEEE Trans. Inf. Theory Ahmed El Alaoui, Aaditya Ramdas, Florent Krzakala, Lenka Zdeborová, Michael I. Jordan
2019	J	`jnl`	Decoding from Pooled Data: Sharp Information-Theoretic Bounds. SIAM J. Math. Data Sci. Ahmed El Alaoui, Aaditya Ramdas, Florent Krzakala, Lenka Zdeborová, Michael I. Jordan
2019	A*	`conf`	Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup. NeurIPS Sebastian Goldt, Madhu Advani, Andrew M. Saxe, Florent Krzakala, Lenka Zdeborová
2019	J	`jnl`	Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup. CoRR Sebastian Goldt, Madhu S. Advani, Andrew M. Saxe, Florent Krzakala, Lenka Zdeborová
2019	J	`jnl`	Exact asymptotics for phase retrieval and compressed sensing with random generative priors. CoRR Benjamin Aubin, Bruno Loureiro, Antoine Baker, Florent Krzakala, Lenka Zdeborová
2019	J	`jnl`	Generalisation dynamics of online learning in over-parameterised neural networks. CoRR Sebastian Goldt, Madhu S. Advani, Andrew M. Saxe, Florent Krzakala, Lenka Zdeborová
2019	J	`jnl`	High-temperature Expansions and Message Passing Algorithms. CoRR Antoine Maillard, Laura Foini, Alejandro Lage Castellanos, Florent Krzakala, Marc Mézard, Lenka Zdeborová
2019	J	`jnl`	Kernel computations from large-scale random features obtained by Optical Processing Units. CoRR Ruben Ohana, Jonas Wacker, Jonathan Dong, Sébastien Marmin, Florent Krzakala, Maurizio Filippone, Laurent Daudet
2019	J	`jnl`	Modelling the influence of data structure on learning in neural networks. CoRR Sebastian Goldt, Marc Mézard, Florent Krzakala, Lenka Zdeborová
2019	J	`jnl`	On the Universality of Noiseless Linear Estimation with Respect to the Measurement Matrix. CoRR Alia Abbara, Antoine Baker, Florent Krzakala, Lenka Zdeborová
2019	J	`jnl`	Optical Reservoir Computing using multiple light scattering for chaotic systems prediction. CoRR Jonathan Dong, Mushegh Rafayelyan, Florent Krzakala, Sylvain Gigan
2019	A*	`conf`	Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models. ICML Stefano Sarao Mannelli, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová
2019	J	`jnl`	Passed & Spurious: analysing descent algorithms and local minima in spiked matrix-tensor model. CoRR Stefano Sarao Mannelli, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová
2019	J	`jnl`	Principled Training of Neural Networks with Direct Feedback Alignment. CoRR Julien Launay, Iacopo Poli, Florent Krzakala
2019	J	`jnl`	Rademacher complexity and spin glasses: A link between the replica and statistical theories of learning. CoRR Alia Abbara, Benjamin Aubin, Florent Krzakala, Lenka Zdeborová
2019	Misc	`conf`	Spectral Method for Multiplexed Phase Retrieval and Application in Optical Imaging in Complex Media. ICASSP Jonathan Dong, Florent Krzakala, Sylvain Gigan
2019	A*	`conf`	The spiked matrix model with generative priors. NeurIPS Benjamin Aubin, Bruno Loureiro, Antoine Maillard, Florent Krzakala, Lenka Zdeborová
2019	J	`jnl`	The spiked matrix model with generative priors. CoRR Benjamin Aubin, Bruno Loureiro, Antoine Maillard, Florent Krzakala, Lenka Zdeborová
2019	J	`jnl`	Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model. CoRR Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Lenka Zdeborová
2019	A*	`conf`	Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models. NeurIPS Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Lenka Zdeborová
2018	J	`jnl`	Approximate Survey Propagation for Statistical Inference. CoRR Fabrizio Antenucci, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová
2018	J	`jnl`	Approximate message-passing for convex optimization with non-separable penalties. CoRR Andre Manoel, Florent Krzakala, Gaël Varoquaux, Bertrand Thirion, Lenka Zdeborová
2018	A*	`conf`	Entropy and mutual information in models of deep neural networks. NeurIPS Marylou Gabrié, Andre Manoel, Clément Luneau, Jean Barbier, Nicolas Macris, Florent Krzakala, Lenka Zdeborová
2018	J	`jnl`	Entropy and mutual information in models of deep neural networks. CoRR Marylou Gabrié, Andre Manoel, Clément Luneau, Jean Barbier, Nicolas Macris, Florent Krzakala, Lenka Zdeborová
2018	B	`conf`	Estimation in the Spiked Wigner Model: A Short Proof of the Replica Formula. ISIT Ahmed El Alaoui, Florent Krzakala
2018	J	`jnl`	Estimation in the Spiked Wigner Model: A Short Proof of the Replica Formula. CoRR Ahmed El Alaoui, Florent Krzakala
2018	J	`jnl`	Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference. CoRR Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová
2018	A*	`conf`	Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models. COLT Jean Barbier, Florent Krzakala, Nicolas Macris, Léo Miolane, Lenka Zdeborová
2018	J	`jnl`	Rank-one matrix estimation: analysis of algorithmic and information theoretic limits by the spatial coupling method. CoRR Jean Barbier, Mohamad Dia, Nicolas Macris, Florent Krzakala, Lenka Zdeborová
2018	—	`conf`	Scaling Up Echo-State Networks With Multiple Light Scattering. SSP Jonathan Dong, Sylvain Gigan, Florent Krzakala, Gilles Wainrib
2018	B	`conf`	The Mutual Information in Random Linear Estimation Beyond i.i.d. Matrices. ISIT Jean Barbier, Nicolas Macris, Antoine Maillard, Florent Krzakala
2018	J	`jnl`	The Mutual Information in Random Linear Estimation Beyond i.i.d. Matrices. CoRR Jean Barbier, Nicolas Macris, Antoine Maillard, Florent Krzakala
2018	A*	`conf`	The committee machine: Computational to statistical gaps in learning a two-layers neural network. NeurIPS Benjamin Aubin, Antoine Maillard, Jean Barbier, Florent Krzakala, Nicolas Macris, Lenka Zdeborová
2018	J	`jnl`	The committee machine: Computational to statistical gaps in learning a two-layers neural network. CoRR Benjamin Aubin, Antoine Maillard, Jean Barbier, Florent Krzakala, Nicolas Macris, Lenka Zdeborová
2017	J	`jnl`	A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines. CoRR Eric W. Tramel, Marylou Gabrié, Andre Manoel, Francesco Caltagirone, Florent Krzakala
2017	J	`jnl`	Approximate Message-Passing Decoder and Capacity Achieving Sparse Superposition Codes. IEEE Trans. Inf. Theory Jean Barbier, Florent Krzakala
2017	J	`jnl`	Constrained Low-rank Matrix Estimation: Phase Transitions, Approximate Message Passing and Applications. CoRR Thibault Lesieur, Florent Krzakala, Lenka Zdeborová
2017	J	`jnl`	Decoding from Pooled Data: Phase Transitions of Message Passing. CoRR Ahmed El Alaoui, Aaditya Ramdas, Florent Krzakala, Lenka Zdeborová, Michael I. Jordan
2017	B	`conf`	Decoding from pooled data: Phase transitions of message passing. ISIT Ahmed El Alaoui, Aaditya Ramdas, Florent Krzakala, Lenka Zdeborová, Michael I. Jordan
2017	J	`jnl`	Finite Size Corrections and Likelihood Ratio Fluctuations in the Spiked Wigner Model. CoRR Ahmed El Alaoui, Florent Krzakala, Michael I. Jordan
2017	A*	`conf`	Information-theoretic thresholds from the cavity method. STOC Amin Coja-Oghlan, Florent Krzakala, Will Perkins, Lenka Zdeborová
2017	J	`jnl`	Multi-Layer Generalized Linear Estimation. CoRR Andre Manoel, Florent Krzakala, Marc Mézard, Lenka Zdeborová
2017	B	`conf`	Multi-layer generalized linear estimation. ISIT Andre Manoel, Florent Krzakala, Marc Mézard, Lenka Zdeborová
2017	J	`jnl`	Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation. CoRR Jean Barbier, Nicolas Macris, Mohamad Dia, Florent Krzakala
2017	J	`jnl`	Performance Limits for Noisy Multimeasurement Vector Problems. IEEE Trans. Signal Process. Junan Zhu, Dror Baron, Florent Krzakala
2017	J	`jnl`	Phase Transitions, Optimal Errors and Optimality of Message-Passing in Generalized Linear Models. CoRR Jean Barbier, Florent Krzakala, Nicolas Macris, Léo Miolane, Lenka Zdeborová
2017	J	`jnl`	Robust Phase Retrieval with the Swept Approximate Message Passing (prSAMP) Algorithm. Image Process. Line Boshra Rajaei, Sylvain Gigan, Florent Krzakala, Laurent Daudet
2017	B	`conf`	Statistical and computational phase transitions in spiked tensor estimation. ISIT Thibault Lesieur, Léo Miolane, Marc Lelarge, Florent Krzakala, Lenka Zdeborová
2017	J	`jnl`	Statistical and computational phase transitions in spiked tensor estimation. CoRR Thibault Lesieur, Léo Miolane, Marc Lelarge, Florent Krzakala, Lenka Zdeborová
2017	—	`conf`	Streaming Bayesian inference: Theoretical limits and mini-batch approximate message-passing. Allerton Andre Manoel, Florent Krzakala, Eric W. Tramel, Lenka Zdeborová
2017	J	`jnl`	Streaming Bayesian inference: theoretical limits and mini-batch approximate message-passing. CoRR Andre Manoel, Florent Krzakala, Eric W. Tramel, Lenka Zdeborová
2016	J	`jnl`	Clustering from Sparse Pairwise Measurements. CoRR Alaa Saade, Marc Lelarge, Florent Krzakala, Lenka Zdeborová
2016	B	`conf`	Clustering from sparse pairwise measurements. ISIT Alaa Saade, Marc Lelarge, Florent Krzakala, Lenka Zdeborová
2016	J	`jnl`	Decoding from Pooled Data: Sharp Information-Theoretic Bounds. CoRR Ahmed El Alaoui, Aaditya Ramdas, Florent Krzakala, Lenka Zdeborová, Michael I. Jordan
2016	J	`jnl`	Fast Phase Retrieval for High Dimensions: A Block-Based Approach. IEEE Signal Process. Lett. Boshra Rajaei, Sylvain Gigan, Florent Krzakala, Laurent Daudet
2016	J	`jnl`	Fast Randomized Semi-Supervised Clustering. CoRR Alaa Saade, Florent Krzakala, Marc Lelarge, Lenka Zdeborová
2016	J	`jnl`	Fast phase retrieval for high dimensions: A block-based approach. CoRR Boshra Rajaei, Sylvain Gigan, Florent Krzakala, Laurent Daudet
2016	J	`jnl`	Inferring Sparsity: Compressed Sensing using Generalized Restricted Boltzmann Machines. CoRR Eric W. Tramel, Andre Manoel, Francesco Caltagirone, Marylou Gabrié, Florent Krzakala
2016	B	`conf`	Inferring sparsity: Compressed sensing using generalized restricted Boltzmann machines. ITW Eric W. Tramel, Andre Manoel, Francesco Caltagirone, Marylou Gabrié, Florent Krzakala
2016	J	`jnl`	Information-theoretic thresholds from the cavity method. CoRR Amin Coja-Oghlan, Florent Krzakala, Will Perkins, Lenka Zdeborová
2016	Misc	`conf`	Intensity-only optical compressive imaging using a multiply scattering material and a double phase retrieval approach. ICASSP Boshra Rajaei, Eric W. Tramel, Sylvain Gigan, Florent Krzakala, Laurent Daudet
2016	J	`jnl`	Mutual Information in Rank-One Matrix Estimation. CoRR Florent Krzakala, Jiaming Xu, Lenka Zdeborová
2016	—	`conf`	Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula. NIPS Jean Barbier, Mohamad Dia, Nicolas Macris, Florent Krzakala, Thibault Lesieur, Lenka Zdeborová
2016	J	`jnl`	Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula. CoRR Jean Barbier, Mohamad Dia, Nicolas Macris, Florent Krzakala, Thibault Lesieur, Lenka Zdeborová
2016	B	`conf`	Mutual information in rank-one matrix estimation. ITW Florent Krzakala, Jiaming Xu, Lenka Zdeborová
2016	J	`jnl`	Performance Limits for Noisy Multi-Measurement Vector Problems. CoRR Junan Zhu, Dror Baron, Florent Krzakala
2016	J	`jnl`	Phase Transitions and Sample Complexity in Bayes-Optimal Matrix Factorization. IEEE Trans. Inf. Theory Yoshiyuki Kabashima, Florent Krzakala, Marc Mézard, Ayaka Sakata, Lenka Zdeborová
2016	—	`conf`	Phase transitions and optimal algorithms in high-dimensional Gaussian mixture clustering. Allerton Thibault Lesieur, Caterina De Bacco, Jess Banks, Florent Krzakala, Cristopher Moore, Lenka Zdeborová
2016	J	`jnl`	Phase transitions and optimal algorithms in high-dimensional Gaussian mixture clustering. CoRR Thibault Lesieur, Caterina De Bacco, Jess Banks, Florent Krzakala, Cristopher Moore, Lenka Zdeborová
2016	J	`jnl`	Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16). CoRR 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, Valerio Cambareri, Cecile Chenot, Vladimir S. Crnojevic, Marie Danková, Kévin Degraux, Jens Eisert, Mohamed-Jalal Fadili, Marylou Gabrié, Nicolas Gac, Daniele Giacobello, Carlos A. Gomez Gonzalez, Adriana Gonzalez, Pierre-Yves Gousenbourger, Mads Græsbøll Christensen, Rémi Gribonval, Stéphanie Guérit, Shaoguang Huang, Paul Irofti, Laurent Jacques, Ulugbek S. Kamilov, Srdan Kitic, Martin Kliesch, Florent Krzakala, John A. Lee, Wenzhi Liao, Tobias Lindstrøm Jensen, Andre Manoel, Hassan Mansour, Ali Mohammad-Djafari, Amirafshar Moshtaghpour, Fred Maurice Ngolè Mboula, Benoît Pairet, Marko Panic, Gabriel Peyré, Aleksandra Pizurica, Pavel Rajmic, Matthieu Roblin, Ingo Roth, Anil Kumar Sao, Pulkit Sharma, Jean-Luc Starck, Eric W. Tramel, Toon van Waterschoot, Dejan Vukobratovic, Li Wang, Benedikt Wirth, Gerhard Wunder, Hongyan Zhang
2016	Misc	`conf`	Random projections through multiple optical scattering: Approximating Kernels at the speed of light. ICASSP Alaa Saade, Francesco Caltagirone, Igor Carron, Laurent Daudet, Angélique Dremeau, Sylvain Gigan, Florent Krzakala
2016	J	`jnl`	Robust phase retrieval with the swept approximate message passing (prSAMP) algorithm. CoRR Boshra Rajaei, Sylvain Gigan, Florent Krzakala, Laurent Daudet
2016	J	`jnl`	Scaling up Echo-State Networks with multiple light scattering. CoRR Jonathan Dong, Sylvain Gigan, Florent Krzakala, Gilles Wainrib
2016	J	`jnl`	The Mutual Information in Random Linear Estimation. CoRR Jean Barbier, Mohamad Dia, Nicolas Macris, Florent Krzakala
2016	—	`conf`	The mutual information in random linear estimation. Allerton Jean Barbier, Mohamad Dia, Nicolas Macris, Florent Krzakala
2015	Misc	`conf`	Adaptive damping and mean removal for the generalized approximate message passing algorithm. ICASSP Jeremy P. Vila, Philip Schniter, Sundeep Rangan, Florent Krzakala, Lenka Zdeborová
2015	J	`jnl`	Approximate Message Passing with Restricted Boltzmann Machine Priors. CoRR Eric W. Tramel, Angélique Drémeau, Florent Krzakala
2015	J	`jnl`	Approximate message-passing decoder and capacity-achieving sparse superposition codes. CoRR Jean Barbier, Florent Krzakala
2015	J	`jnl`	Intensity-only optical compressive imaging using a multiply scattering material : a double phase retrieval system. CoRR Boshra Rajaei, Eric W. Tramel, Sylvain Gigan, Florent Krzakala, Laurent Daudet
2015	—	`conf`	MMSE of probabilistic low-rank matrix estimation: Universality with respect to the output channel. Allerton Thibault Lesieur, Florent Krzakala, Lenka Zdeborová
2015	J	`jnl`	MMSE of probabilistic low-rank matrix estimation: Universality with respect to the output channel. CoRR Thibault Lesieur, Florent Krzakala, Lenka Zdeborová
2015	—	`conf`	Matrix Completion from Fewer Entries: Spectral Detectability and Rank Estimation. NIPS Alaa Saade, Florent Krzakala, Lenka Zdeborová
2015	J	`jnl`	Matrix Completion from Fewer Entries: Spectral Detectability and Rank Estimation. CoRR Alaa Saade, Florent Krzakala, Lenka Zdeborová
2015	J	`jnl`	Phase Transitions in Sparse PCA. CoRR Thibault Lesieur, Florent Krzakala, Lenka Zdeborová
2015	Misc	`conf`	Phase recovery from a Bayesian point of view: The variational approach. ICASSP Angélique Dremeau, Florent Krzakala
2015	B	`conf`	Phase transitions in sparse PCA. ISIT Thibault Lesieur, Florent Krzakala, Lenka Zdeborová
2015	J	`jnl`	Random Projections through multiple optical scattering: Approximating kernels at the speed of light. CoRR Alaa Saade, Francesco Caltagirone, Igor Carron, Laurent Daudet, Angélique Drémeau, Sylvain Gigan, Florent Krzakala
2015	J	`jnl`	Scampi: a robust approximate message-passing framework for compressive imaging. CoRR Jean Barbier, Eric W. Tramel, Florent Krzakala
2015	J	`jnl`	Spectral Detection in the Censored Block Model. CoRR Alaa Saade, Florent Krzakala, Marc Lelarge, Lenka Zdeborová
2015	J	`jnl`	Spectral Detection on Sparse Hypergraphs. CoRR Maria Chiara Angelini, Francesco Caltagirone, Florent Krzakala, Lenka Zdeborová
2015	B	`conf`	Spectral detection in the censored block model. ISIT Alaa Saade, Marc Lelarge, Florent Krzakala, Lenka Zdeborová
2015	—	`conf`	Spectral detection on sparse hypergraphs. Allerton Maria Chiara Angelini, Francesco Caltagirone, Florent Krzakala, Lenka Zdeborová
2015	J	`jnl`	Statistical physics of inference: Thresholds and algorithms. CoRR Lenka Zdeborová, Florent Krzakala
2015	A*	`conf`	Swept Approximate Message Passing for Sparse Estimation. ICML Andre Manoel, Florent Krzakala, Eric W. Tramel, Lenka Zdeborová
2015	—	`conf`	Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy. NIPS Marylou Gabrié, Eric W. Tramel, Florent Krzakala
2015	J	`jnl`	Training Restricted Boltzmann Machines via the Thouless-Anderson-Palmer Free Energy. CoRR Marylou Gabrié, Eric W. Tramel, Florent Krzakala
2014	J	`jnl`	Adaptive Damping and Mean Removal for the Generalized Approximate Message Passing Algorithm. CoRR Jeremy P. Vila, Philip Schniter, Sundeep Rangan, Florent Krzakala, Lenka Zdeborová
2014	J	`jnl`	On Convergence of Approximate Message Passing. CoRR Francesco Caltagirone, Florent Krzakala, Lenka Zdeborová
2014	B	`conf`	On convergence of approximate message passing. ISIT Francesco Caltagirone, Lenka Zdeborová, Florent Krzakala
2014	J	`jnl`	Phase recovery from a Bayesian point of view: the variational approach. CoRR Angélique Dremeau, Florent Krzakala
2014	J	`jnl`	Phase transitions and sample complexity in Bayes-optimal matrix factorization. CoRR Yoshiyuki Kabashima, Florent Krzakala, Marc Mézard, Ayaka Sakata, Lenka Zdeborová
2014	J	`jnl`	Replica Analysis and Approximate Message Passing Decoder for Superposition Codes. CoRR Jean Barbier, Florent Krzakala
2014	B	`conf`	Replica analysis and approximate message passing decoder for superposition codes. ISIT Jean Barbier, Florent Krzakala
2014	J	`jnl`	Reweighted Belief Propagation and Quiet Planting for Random K-SAT. J. Satisf. Boolean Model. Comput. Florent Krzakala, Marc Mézard, Lenka Zdeborová
2014	J	`jnl`	Sparse Estimation with the Swept Approximated Message-Passing Algorithm. CoRR Andre Manoel, Florent Krzakala, Eric W. Tramel, Lenka Zdeborová
2014	J	`jnl`	Spectral Clustering of Graphs with the Bethe Hessian. CoRR Alaa Saade, Florent Krzakala, Lenka Zdeborová
2014	—	`conf`	Spectral Clustering of graphs with the Bethe Hessian. NIPS Alaa Saade, Florent Krzakala, Lenka Zdeborová
2014	J	`jnl`	Spectral density of the non-backtracking operator. CoRR Alaa Saade, Florent Krzakala, Lenka Zdeborová
2014	J	`jnl`	Variational Free Energies for Compressed Sensing. CoRR Florent Krzakala, Andre Manoel, Eric W. Tramel, Lenka Zdeborová
2014	B	`conf`	Variational free energies for compressed sensing. ISIT Florent Krzakala, Andre Manoel, Eric W. Tramel, Lenka Zdeborová
2013	—	`conf`	Blind Calibration in Compressed Sensing using Message Passing Algorithms. NIPS Christophe Schülke, Francesco Caltagirone, Florent Krzakala, Lenka Zdeborová
2013	J	`jnl`	Blind Calibration in Compressed Sensing using Message Passing Algorithms. CoRR Christophe Schülke, Francesco Caltagirone, Florent Krzakala, Lenka Zdeborová
2013	J	`jnl`	Compressed Sensing under Matrix Uncertainty: Optimum Thresholds and Robust Approximate Message Passing CoRR Florent Krzakala, Marc Mézard, Lenka Zdeborová
2013	J	`jnl`	Compressed sensing and Approximate Message Passing with spatially-coupled Fourier and Hadamard matrices. CoRR Jean Barbier, Florent Krzakala, Christophe Schülke
2013	Misc	`conf`	Compressed sensing under matrix uncertainty: Optimum thresholds and robust approximate message passing. ICASSP Florent Krzakala, Marc Mézard, Lenka Zdeborová
2013	J	`jnl`	Non-adaptive pooling strategies for detection of rare faulty items CoRR Pan Zhang, Florent Krzakala, Marc Mézard, Lenka Zdeborová
2013	—	`conf`	Non-adaptive pooling strategies for detection of rare faulty items. ICC Workshops Pan Zhang, Florent Krzakala, Marc Mézard, Lenka Zdeborová
2013	J	`jnl`	Phase Diagram and Approximate Message Passing for Blind Calibration and Dictionary Learning CoRR Florent Krzakala, Marc Mézard, Lenka Zdeborová
2013	B	`conf`	Phase diagram and approximate message passing for blind calibration and dictionary learning. ISIT Florent Krzakala, Marc Mézard, Lenka Zdeborová
2013	J	`jnl`	Robust error correction for real-valued signals via message-passing decoding and spatial coupling CoRR Jean Barbier, Florent Krzakala, Lenka Zdeborová, Pan Zhang
2013	B	`conf`	Robust error correction for real-valued signals via message-passing decoding and spatial coupling. ITW Jean Barbier, Florent Krzakala, Lenka Zdeborová, Pan Zhang
2013	J	`jnl`	Spectral redemption: clustering sparse networks. CoRR Florent Krzakala, Cristopher Moore, Elchanan Mossel, Joe Neeman, Allan Sly, Lenka Zdeborová, Pan Zhang
2013	J	`jnl`	The hard-core model on random graphs revisited. CoRR Jean Barbier, Florent Krzakala, Lenka Zdeborová, Pan Zhang
2012	J	`jnl`	Belief Propagation Reconstruction for Discrete Tomography CoRR Emmanuelle Gouillart, Florent Krzakala, Marc Mézard, Lenka Zdeborová
2012	J	`jnl`	Comparative Study for Inference of Hidden Classes in Stochastic Block Models CoRR Pan Zhang, Florent Krzakala, Jörg Reichardt, Lenka Zdeborová
2012	J	`jnl`	Compressed Sensing of Approximately-Sparse Signals: Phase Transitions and Optimal Reconstruction CoRR Jean Barbier, Florent Krzakala, Marc Mézard, Lenka Zdeborová
2012	—	`conf`	Compressed sensing of approximately-sparse signals: Phase transitions and optimal reconstruction. Allerton Conference Jean Barbier, Florent Krzakala, Marc Mézard, Lenka Zdeborová
2012	J	`jnl`	Model Selection for Degree-corrected Block Models CoRR Xiaoran Yan, Jacob E. Jensen, Florent Krzakala, Cristopher Moore, Cosma Rohilla Shalizi, Lenka Zdeborová, Pan Zhang, Yaojia Zhu
2012	J	`jnl`	Probabilistic Reconstruction in Compressed Sensing: Algorithms, Phase Diagrams, and Threshold Achieving Matrices CoRR Florent Krzakala, Marc Mézard, François Sausset, Yifan Sun, Lenka Zdeborová
2012	J	`jnl`	The Quantum Adiabatic Algorithm applied to random optimization problems: the quantum spin glass perspective CoRR Victor Bapst, Laura Foini, Florent Krzakala, Guilhem Semerjian, Francesco Zamponi
2011	J	`jnl`	Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications CoRR Aurélien Decelle, Florent Krzakala, Cristopher Moore, Lenka Zdeborová
2011	J	`jnl`	Phase transition in the detection of modules in sparse networks CoRR Aurélien Decelle, Florent Krzakala, Cristopher Moore, Lenka Zdeborová
2011	J	`jnl`	Quiet Planting in the Locked Constraint Satisfaction Problems. SIAM J. Discret. Math. Lenka Zdeborová, Florent Krzakala
2011	J	`jnl`	Statistical physics-based reconstruction in compressed sensing CoRR Florent Krzakala, Marc Mézard, François Sausset, Yifan Sun, Lenka Zdeborová
2009	J	`jnl`	First-order transitions and the performance of quantum algorithms in random optimization problems. CoRR Thomas Jörg, Florent Krzakala, Guilhem Semerjian, Francesco Zamponi
2009	J	`jnl`	Hiding Quiet Solutions in Random Constraint Satisfaction Problems CoRR Florent Krzakala, Lenka Zdeborová
2009	J	`jnl`	Quantum energy gaps and first-order mean-field-like transitions CoRR Thomas Jörg, Florent Krzakala, Jorge Kurchan, Anthony C. Maggs, J. Pujos
2009	J	`jnl`	Quiet Planting in the Locked Constraint Satisfaction Problems CoRR Lenka Zdeborová, Florent Krzakala
2007	J	`jnl`	A Landscape Analysis of Constraint Satisfaction Problems CoRR Florent Krzakala, Jorge Kurchan
2007	J	`jnl`	Constraint optimization and landscapes CoRR Florent Krzakala, Jorge Kurchan
2007	J	`jnl`	Gibbs states and the set of solutions of random constraint satisfaction problems. Proc. Natl. Acad. Sci. USA Florent Krzakala, Andrea Montanari, Federico Ricci-Tersenghi, Guilhem Semerjian, Lenka Zdeborová
2007	J	`jnl`	Phase Transitions and Computational Difficulty in Random Constraint Satisfaction Problems CoRR Florent Krzakala, Lenka Zdeborová
2007	J	`jnl`	Phase Transitions in the Coloring of Random Graphs CoRR Lenka Zdeborová, Florent Krzakala
2006	J	`jnl`	Gibbs States and the Set of Solutions of Random Constraint Satisfaction Problems CoRR Florent Krzakala, Andrea Montanari, Federico Ricci-Tersenghi, Guilhem Semerjian, Lenka Zdeborová
2004	J	`jnl`	Threshold values, stability analysis and high-q asymptotics for the coloring problem on random graphs CoRR Florent Krzakala, Andrea Pagnani, Martin Weigt