| 2026 | COLT | Provable Learning of Random Hierarchy Models and Hierarchical Shallow-to-Deep Chaining. | Yunwei Ren, Yatin Dandi, Florent Krzakala, Jason D. Lee |
| 2025 | AISTATS | 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 |
| 2025 | AISTATS | A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs. | Kasimir Tanner, Matteo Vilucchio, Bruno Loureiro, Florent Krzakala |
| 2025 | AISTATS | Fundamental computational limits of weak learnability in high-dimensional multi-index models. | Emanuele Troiani, Yatin Dandi, Leonardo Defilippis, Lenka Zdeborov, Bruno Loureiro, Florent Krzakala |
| 2025 | COLT | Fundamental Limits of Matrix Sensing: Exact Asymptotics, Universality, and Applications. | Yizhou Xu, Antoine Maillard, Lenka Zdeborov, Florent Krzakala |
| 2025 | ICML | 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 Zdeborov |
| 2024 | AISTATS | Asymptotic Characterisation of the Performance of Robust Linear Regression in the Presence of Outliers. | Matteo Vilucchio, Emanuele Troiani, Vittorio Erba, Florent Krzakala |
| 2024 | COLT | Fundamental Limits of Non-Linear Low-Rank Matrix Estimation. | Pierre Mergny, Justin Ko, Florent Krzakala, Lenka Zdeborov |
| 2024 | ICLR | Analysis of Learning a Flow-based Generative Model from Limited Sample Complexity. | Hugo Cui, Florent Krzakala, Eric Vanden-Eijnden, Lenka Zdeborov |
| 2024 | ICML | Online Learning and Information Exponents: The Importance of Batch size & Time/Complexity Tradeoffs. | Luca Arnaboldi, Yatin Dandi, Florent Krzakala, Bruno Loureiro, Luca Pesce, Ludovic Stephan |
| 2024 | ICML | Asymptotics of feature learning in two-layer networks after one gradient-step. | Hugo Cui, Luca Pesce, Yatin Dandi, Florent Krzakala, Yue M. Lu, Lenka Zdeborov, Bruno Loureiro |
| 2024 | ICML | 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, Luca Pesce, Lenka Zdeborov, Florent Krzakala |
| 2024 | ICML | Spectral Phase Transition and Optimal PCA in Block-Structured Spiked Models. | Pierre Mergny, Justin Ko, Florent Krzakala |
| 2024 | UAI | Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression. | Lucas Clart, Adrien Vandenbroucque, Guillaume Dalle, Bruno Loureiro, Florent Krzakala, Lenka Zdeborov |
| 2023 | AISTATS | On double-descent in uncertainty quantification in overparametrized models. | Lucas Clart, Bruno Loureiro, Florent Krzakala, Lenka Zdeborov |
| 2023 | COLT | From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks. | Luca Arnaboldi, Ludovic Stephan, Florent Krzakala, Bruno Loureiro |
| 2023 | ICML | Bayes-optimal Learning of Deep Random Networks of Extensive-width. | Hugo Cui, Florent Krzakala, Lenka Zdeborov |
| 2023 | ICML | 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 |
| 2023 | ITW | Compressed sensing with ℓ0-norm: statistical physics analysis & algorithms for signal recovery. | Damien Barbier, Carlo Lucibello, Luca Saglietti, Florent Krzakala, Lenka Zdeborov |
| 2023 | UAI | Expectation consistency for calibration of neural networks. | Lucas Clart, Bruno Loureiro, Florent Krzakala, Lenka Zdeborov |
| 2022 | ICASSP | Adversarial Robustness by Design Through Analog Computing And Synthetic Gradients. | Alessandro Cappelli, Ruben Ohana, Julien Launay, Laurent Meunier, Iacopo Poli, Florent Krzakala |
| 2022 | ICML | Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension. | Bruno Loureiro, Cdric Gerbelot, Maria Refinetti, Gabriele Sicuro, Florent Krzakala |
| 2022 | ISIT | Secure Coding via Gaussian Random Fields. | Ali Bereyhi, Bruno Loureiro, Florent Krzakala, Ralf R. Mller, Hermann Schulz-Baldes |
| 2021 | ICML | Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed. | Maria Refinetti, Sebastian Goldt, Florent Krzakala, Lenka Zdeborov |
| 2020 | COLT | Asymptotic Errors for High-Dimensional Convex Penalized Linear Regression beyond Gaussian Matrices. | Cdric Gerbelot, Alia Abbara, Florent Krzakala |
| 2020 | ICASSP | Kernel Computations from Large-Scale Random Features Obtained by Optical Processing Units. | Ruben Ohana, Jonas Wacker, Jonathan Dong, Sbastien Marmin, Florent Krzakala, Maurizio Filippone, Laurent Daudet |
| 2020 | ICML | Double Trouble in Double Descent: Bias and Variance(s) in the Lazy Regime. | Stphane d'Ascoli, Maria Refinetti, Giulio Biroli, Florent Krzakala |
| 2020 | ICML | Generalisation error in learning with random features and the hidden manifold model. | Federica Gerace, Bruno Loureiro, Florent Krzakala, Marc Mzard, Lenka Zdeborov |
| 2020 | ICML | The Role of Regularization in Classification of High-dimensional Noisy Gaussian Mixture. | Francesca Mignacco, Florent Krzakala, Yue M. Lu, Pierfrancesco Urbani, Lenka Zdeborov |
| 2019 | ICASSP | Spectral Method for Multiplexed Phase Retrieval and Application in Optical Imaging in Complex Media. | Jonathan Dong, Florent Krzakala, Sylvain Gigan |
| 2019 | ICML | Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models. | Stefano Sarao Mannelli, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborov |
| 2018 | COLT | Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models. | Jean Barbier, Florent Krzakala, Nicolas Macris, Lo Miolane, Lenka Zdeborov |
| 2018 | ISIT | Estimation in the Spiked Wigner Model: A Short Proof of the Replica Formula. | Ahmed El Alaoui, Florent Krzakala |
| 2018 | ISIT | The Mutual Information in Random Linear Estimation Beyond i.i.d. Matrices. | Jean Barbier, Nicolas Macris, Antoine Maillard, Florent Krzakala |
| 2017 | ISIT | Decoding from pooled data: Phase transitions of message passing. | Ahmed El Alaoui, Aaditya Ramdas, Florent Krzakala, Lenka Zdeborov, Michael I. Jordan |
| 2017 | ISIT | Statistical and computational phase transitions in spiked tensor estimation. | Thibault Lesieur, Lo Miolane, Marc Lelarge, Florent Krzakala, Lenka Zdeborov |
| 2017 | ISIT | Multi-layer generalized linear estimation. | Andre Manoel, Florent Krzakala, Marc Mzard, Lenka Zdeborov |
| 2017 | STOC | Information-theoretic thresholds from the cavity method. | Amin Coja-Oghlan, Florent Krzakala, Will Perkins, Lenka Zdeborov |
| 2016 | ICASSP | 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 |
| 2016 | ICASSP | Random projections through multiple optical scattering: Approximating Kernels at the speed of light. | Alaa Saade, Francesco Caltagirone, Igor Carron, Laurent Daudet, Anglique Dremeau, Sylvain Gigan, Florent Krzakala |
| 2016 | ISIT | Clustering from sparse pairwise measurements. | Alaa Saade, Marc Lelarge, Florent Krzakala, Lenka Zdeborov |
| 2016 | ITW | Mutual information in rank-one matrix estimation. | Florent Krzakala, Jiaming Xu, Lenka Zdeborov |
| 2016 | ITW | Inferring sparsity: Compressed sensing using generalized restricted Boltzmann machines. | Eric W. Tramel, Andre Manoel, Francesco Caltagirone, Marylou Gabri, Florent Krzakala |
| 2015 | ICASSP | Phase recovery from a Bayesian point of view: The variational approach. | Anglique Dremeau, Florent Krzakala |
| 2015 | ICASSP | Adaptive damping and mean removal for the generalized approximate message passing algorithm. | Jeremy P. Vila, Philip Schniter, Sundeep Rangan, Florent Krzakala, Lenka Zdeborov |
| 2015 | ICML | Swept Approximate Message Passing for Sparse Estimation. | Andre Manoel, Florent Krzakala, Eric W. Tramel, Lenka Zdeborov |
| 2015 | ISIT | Phase transitions in sparse PCA. | Thibault Lesieur, Florent Krzakala, Lenka Zdeborov |
| 2015 | ISIT | Spectral detection in the censored block model. | Alaa Saade, Marc Lelarge, Florent Krzakala, Lenka Zdeborov |
| 2014 | ISIT | Replica analysis and approximate message passing decoder for superposition codes. | Jean Barbier, Florent Krzakala |
| 2014 | ISIT | On convergence of approximate message passing. | Francesco Caltagirone, Lenka Zdeborov, Florent Krzakala |
| 2014 | ISIT | Variational free energies for compressed sensing. | Florent Krzakala, Andre Manoel, Eric W. Tramel, Lenka Zdeborov |
| 2013 | ICASSP | Compressed sensing under matrix uncertainty: Optimum thresholds and robust approximate message passing. | Florent Krzakala, Marc Mzard, Lenka Zdeborov |
| 2013 | ISIT | Phase diagram and approximate message passing for blind calibration and dictionary learning. | Florent Krzakala, Marc Mzard, Lenka Zdeborov |
| 2013 | ITW | Robust error correction for real-valued signals via message-passing decoding and spatial coupling. | Jean Barbier, Florent Krzakala, Lenka Zdeborov, Pan Zhang |