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Storage capacity in symmetric binary perceptrons, , and . (2019)cite arxiv:1901.00314Comment: 18 + 7 pages.Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization., , , and . NeurIPS, (2020)Tree-AMP: Compositional Inference with Tree Approximate Message Passing., , , and . J. Mach. Learn. Res., (2023)Rademacher complexity and spin glasses: A link between the replica and statistical theories of learning., , , and . MSML, volume 107 of Proceedings of Machine Learning Research, page 27-54. PMLR, (2020)Mean-field methods and algorithmic perspectives for high-dimensional machine learning. (Méthodes à champ moyen et perspectives algorithmiques pour l'apprentissage automatique en haute dimension).. University of Paris-Saclay, France, (2020)The spiked matrix model with generative priors., , , , and . NeurIPS, page 8364-8375. (2019)Rademacher complexity and spin glasses: A link between the replica and statistical theories of learning., , , and . CoRR, (2019)Exact asymptotics for phase retrieval and compressed sensing with random generative priors., , , , and . CoRR, (2019)The committee machine: Computational to statistical gaps in learning a two-layers neural network., , , , , and . NeurIPS, page 3227-3238. (2018)TRAMP: Compositional Inference with TRee Approximate Message Passing., , , and . CoRR, (2020)