| 2026 | COLT | Rigorous Asymptotics for First-Order Algorithms Through the Dynamical Cavity Method. | Yatin Dandi, David Gamarnik, Francisco Pernice, Lenka Zdeborov |
| 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 | Counting in Small Transformers: The Delicate Interplay between Attention and Feed-Forward Layers. | Freya Behrens, Luca Biggio, Lenka Zdeborov |
| 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 |
| 2025 | UAI | Building Conformal Prediction Intervals with Approximate Message Passing. | Lucas Clart, Lenka Zdeborov |
| 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 | 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 | 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 | ICML | Bayes-optimal Learning of Deep Random Networks of Extensive-width. | Hugo Cui, Florent Krzakala, Lenka Zdeborov |
| 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 |
| 2021 | ICML | Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed. | Maria Refinetti, Sebastian Goldt, Florent Krzakala, Lenka Zdeborov |
| 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 | 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 |
| 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 | 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 |
| 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 | 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 |
| 2012 | SODA | The condensation transition in random hypergraph 2-coloring. | Amin Coja-Oghlan, Lenka Zdeborov |