| Optimal dimension dependence of the Metropolis-adjusted Langevin algorithm S Chewi, C Lu, K Ahn, X Cheng, T Le Gouic, P Rigollet Conference on Learning Theory, 1260-1300, 2021 | 87 | 2021 |
| SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence S Chewi, T Le Gouic, C Lu, T Maunu, P Rigollet Advances in Neural Information Processing Systems 33, 2098-2109, 2020 | 85 | 2020 |
| Exponential ergodicity of mirror-Langevin diffusions S Chewi, T Le Gouic, C Lu, T Maunu, P Rigollet, A Stromme Advances in Neural Information Processing Systems 33, 19573-19585, 2020 | 59 | 2020 |
| Contextual stochastic block model: Sharp thresholds and contiguity C Lu, S Sen Journal of Machine Learning Research 24 (54), 1-34, 2023 | 27 | 2023 |
| The query complexity of sampling from strongly log-concave distributions in one dimension S Chewi, PR Gerber, C Lu, T Le Gouic, P Rigollet Conference on Learning Theory, 2041-2059, 2022 | 19 | 2022 |
| Robust nonparametric difference-in-differences estimation C Lu, X Nie, S Wager arXiv e-prints, arXiv: 1905.11622, 2019 | 17 | 2019 |
| Fisher information lower bounds for sampling S Chewi, P Gerber, H Lee, C Lu International Conference on Algorithmic Learning Theory, 375-410, 2023 | 15 | 2023 |
| Query lower bounds for log-concave sampling S Chewi, J de Dios Pont, J Li, C Lu, S Narayanan Journal of the ACM 71 (4), 1-42, 2024 | 11 | 2024 |
| Nonparametric heterogeneous treatment effect estimation in repeated cross sectional designs X Nie, C Lu, S Wager arXiv preprint arXiv:1905.11622, 2019 | 10 | 2019 |
| Rejection sampling from shape-constrained distributions in sublinear time S Chewi, PR Gerber, C Lu, T Le Gouic, P Rigollet International conference on artificial intelligence and statistics, 2249-2265, 2022 | 5 | 2022 |
| Upper and Lower Bounds for Sampling C Lu Massachusetts Institute of Technology, 2023 | 3 | 2023 |
