Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent. - Jason M. Altschuler; Sinho Chewi; Patrik Gerber; Austin J. Stromme (NeurIPS, 2021)

Rejection sampling from shape-constrained distributions in sublinear time. - Sinho Chewi; Patrik R. Gerber; Chen Lu 002; Thibaut Le Gouic; Philippe Rigollet (AISTATS, 2022)

The query complexity of sampling from strongly log-concave distributions in one dimension. - Sinho Chewi; Patrik R. Gerber; Chen Lu 002; Thibaut Le Gouic; Philippe Rigollet (COLT, 2022)

Gaussian discrepancy: A probabilistic relaxation of vector balancing. - Sinho Chewi; Patrik Gerber; Philippe Rigollet; Paxton Turner (Discret. Appl. Math., 2022)

Fisher information lower bounds for sampling. - Sinho Chewi; Patrik Gerber; Holden Lee; Chen Lu 002 (ALT, 2023)

Minimax optimal testing by classification. - Patrik R. Gerber; Yanjun Han; Yury Polyanskiy (COLT, 2023)

Kernel-Based Tests for Likelihood-Free Hypothesis Testing. - Patrik Róbert Gerber; Tianze Jiang; Yury Polyanskiy; Rui Sun (NeurIPS, 2023)

Likelihood-Free Hypothesis Testing. - Patrik Róbert Gerber; Yury Polyanskiy (IEEE Trans. Inf. Theory, 2024)