The estimation error of general first order methods. - Michael Celentano; Andrea Montanari; Yuchen Wu 002 (COLT, 2020)

The Lasso with general Gaussian designs with applications to hypothesis testing. - Michael Celentano; Andrea Montanari; Yuting Wei 001 (CoRR, 2020)

Minimum complexity interpolation in random features models. - Michael Celentano; Theodor Misiakiewicz; Andrea Montanari (CoRR, 2021)

Local convexity of the TAP free energy and AMP convergence for Z2-synchronization. - Michael Celentano; Zhou Fan; Song Mei (CoRR, 2021)

Sudakov-Fernique post-AMP, and a new proof of the local convexity of the TAP free energy. - Michael Celentano (CoRR, 2022)

Maximum Mean Discrepancy Meets Neural Networks: The Radon-Kolmogorov-Smirnov Test. - Seunghoon Paik; Michael Celentano; Alden Green; Ryan J. Tibshirani (CoRR, 2023)

Mean-field variational inference with the TAP free energy: Geometric and statistical properties in linear models. - Michael Celentano; Zhou Fan; Licong Lin; Song Mei (CoRR, 2023)

State evolution beyond first-order methods I: Rigorous predictions and finite-sample guarantees. - Michael Celentano; Chen Cheng; Ashwin Pananjady; Kabir Aladin Verchand (CoRR, 2025)