| 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 |
| 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 | Asymptotics of Learning with Deep Structured (Random) Features. | Dominik Schrder, Daniil Dmitriev, Hugo Cui, Bruno Loureiro |
| 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 | 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 | ICML | Deterministic equivalent and error universality of deep random features learning. | Dominik Schrder, Hugo Cui, Daniil Dmitriev, Bruno Loureiro |
| 2023 | UAI | Expectation consistency for calibration of neural networks. | Lucas Clart, Bruno Loureiro, Florent Krzakala, Lenka Zdeborov |
| 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 |
| 2020 | ICML | Generalisation error in learning with random features and the hidden manifold model. | Federica Gerace, Bruno Loureiro, Florent Krzakala, Marc Mzard, Lenka Zdeborov |
| 2017 | MOBICOM | EVERUN: Enabling Power Consumption Monitoring in Underwater Networking Platforms. | Giannis Kazdaridis, Stratos Keranidis, Polychronis Symeonidis, Paulo Sousa Dias, Pedro Gonalves, Bruno Loureiro, Petrika Gjanci, Chiara Petrioli |