{"total":16,"rows":[{"id":"2308.14085","title":"Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective","created":"2023-08-27","cited_by_count":26,"area":null},{"id":"2103.04902","title":"Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem","created":"2021-03-08","cited_by_count":23,"area":null},{"id":"2408.03733","title":"Bayes-optimal learning of an extensive-width neural network from quadratically many samples","created":"2024-08-07","cited_by_count":23,"area":null},{"id":"2106.10744","title":"On the Cryptographic Hardness of Learning Single Periodic Neurons","created":"2021-06-20","cited_by_count":20,"area":null},{"id":"2305.18502","title":"Escaping mediocrity: how two-layer networks learn hard generalized linear models with SGD","created":"2023-05-29","cited_by_count":15,"area":null},{"id":"2110.10210","title":"Long Random Matrices and Tensor Unfolding","created":"2021-10-19","cited_by_count":10,"area":null},{"id":"2208.09550","title":"Sudakov-Fernique post-AMP, and a new proof of the local convexity of the TAP free energy","created":"2022-08-19","cited_by_count":9,"area":null},{"id":"2406.01589","title":"Tilting the Odds at the Lottery: the Interplay of Overparameterisation and Curricula in Neural Networks","created":"2024-06-03","cited_by_count":9,"area":null},{"id":"2301.07737","title":"Catapult Dynamics and Phase Transitions in Quadratic Nets","created":"2023-01-18","cited_by_count":8,"area":null},{"id":"2102.11755","title":"Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problems","created":"2021-02-23","cited_by_count":5,"area":null},{"id":"2306.00809","title":"Initial Guessing Bias: How Untrained Networks Favor Some Classes","created":"2023-06-01","cited_by_count":5,"area":null},{"id":"2309.04788","title":"Stochastic Gradient Descent outperforms Gradient Descent in recovering a high-dimensional signal in a glassy energy landscape","created":"2023-09-09","cited_by_count":3,"area":null},{"id":"2410.18858","title":"Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-dimensional Tokens","created":"2024-10-24","cited_by_count":3,"area":null},{"id":"2510.18435","title":"Overparametrization bends the landscape: BBP transitions at initialization in simple Neural Networks","created":"2025-10-21","cited_by_count":2,"area":null},{"id":"2311.15221","title":"The Local Landscape of Phase Retrieval Under Limited Samples","created":"2023-11-26","cited_by_count":1,"area":null},{"id":"2602.17779","title":"Topological Exploration of High-Dimensional Empirical Risk Landscapes: general approach, and applications to phase retrieval","created":"2026-02-19","cited_by_count":1,"area":null}],"next_cursor":null}