| The lasso with general gaussian designs with applications to hypothesis testing M Celentano, A Montanari, Y Wei The Annals of Statistics 51 (5), 2194-2220, 2023 | 103 | 2023 |
| Fundamental barriers to high-dimensional regression with convex penalties M Celentano, A Montanari The Annals of Statistics 50 (1), 170-196, 2022 | 67 | 2022 |
| The estimation error of general first order methods M Celentano, A Montanari, Y Wu Conference on Learning Theory, 1078-1141, 2020 | 59 | 2020 |
| The high-dimensional asymptotics of first order methods with random data M Celentano, C Cheng, A Montanari arXiv preprint arXiv:2112.07572, 2021 | 49 | 2021 |
| Local convexity of the TAP free energy and AMP convergence for -synchronization M Celentano, Z Fan, S Mei The Annals of Statistics 51 (2), 519-546, 2023 | 35 | 2023 |
| Sudakov–Fernique post-AMP, and a new proof of the local convexity of the TAP free energy M Celentano The Annals of Probability 52 (3), 923-954, 2024 | 23 | 2024 |
| CAD: Debiasing the Lasso with inaccurate covariate model M Celentano, A Montanari arXiv preprint arXiv:2107.14172, 2021 | 12 | 2021 |
| Approximate separability of symmetrically penalized least squares in high dimensions: characterization and consequences M Celentano Information and Inference: A Journal of the IMA 10 (3), 1105-1165, 2021 | 8 | 2021 |
| Minimum complexity interpolation in random features models M Celentano, T Misiakiewicz, A Montanari arXiv preprint arXiv:2103.15996, 2021 | 7 | 2021 |
| Mean-field variational inference with the TAP free energy: Geometric and statistical properties in linear models M Celentano, Z Fan, L Lin, S Mei arXiv preprint arXiv:2311.08442, 2023 | 6 | 2023 |
| Maximum mean discrepancy meets neural networks: The radon-kolmogorov-smirnov test S Paik, M Celentano, A Green, RJ Tibshirani arXiv preprint arXiv:2309.02422, 2023 | 4 | 2023 |
| Challenges of the inconsistency regime: Novel debiasing methods for missing data models M Celentano, MJ Wainwright arXiv preprint arXiv:2309.01362, 2023 | 3 | 2023 |
| Exact and efficient phylodynamic simulation from arbitrarily large populations M Celentano, WS DeWitt, S Prillo, YS Song ArXiv, 2024 | 2 | 2024 |
| Correlation adjusted debiased Lasso: debiasing the Lasso with inaccurate covariate model M Celentano, A Montanari Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2024 | 1 | 2024 |
| THE ANNALS PC BELLEC, C ZHANG, A FINKE, AH THIERY, A ROHDE, ... The Annals of Statistics 51 (2), 2023 | | 2023 |
| Topics in Exact Asymptotics for High-Dimensional Regression M Celentano Stanford University, 2021 | | 2021 |
