| What Makes Good In-Context Examples for GPT-? J Liu, D Shen, Y Zhang, B Dolan, L Carin, W Chen arXiv preprint arXiv:2101.06804, 2021 | 1195 | 2021 |
| Club: A contrastive log-ratio upper bound of mutual information P Cheng, W Hao, S Dai, J Liu, Z Gan, L Carin International conference on machine learning, 1779-1788, 2020 | 356 | 2020 |
| Fast sparse classification for generalized linear and additive models J Liu, C Zhong, M Seltzer, C Rudin Proceedings of machine learning research 151, 9304, 2022 | 20 | 2022 |
| Representing graphs via Gromov-Wasserstein factorization H Xu, J Liu, D Luo, L Carin IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (1), 999-1016, 2022 | 16 | 2022 |
| FasterRisk: Fast and accurate interpretable risk scores J Liu, C Zhong, B Li, M Seltzer, C Rudin Advances in Neural Information Processing Systems 35, 17760-17773, 2022 | 14 | 2022 |
| Amazing things come from having many good models C Rudin, C Zhong, L Semenova, M Seltzer, R Parr, J Liu, S Katta, ... arXiv preprint arXiv:2407.04846, 2024 | 7 | 2024 |
| Exploring and interacting with the set of good sparse generalized additive models C Zhong, Z Chen, J Liu, M Seltzer, C Rudin Advances in neural information processing systems 36, 2024 | 5 | 2024 |
| OKRidge: Scalable Optimal k-Sparse Ridge Regression J Liu, S Rosen, C Zhong, C Rudin Thirty-seventh Conference on Neural Information Processing Systems, 2023 | 3* | 2023 |
| Fast and Interpretable Mortality Risk Scores for Critical Care Patients CQ Zhu, M Tian, L Semenova, J Liu, J Xu, J Scarpa, C Rudin arXiv preprint arXiv:2311.13015, 2023 | 1 | 2023 |
| FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models J Liu, R Zhang, C Rudin arXiv preprint arXiv:2410.19081, 2024 | | 2024 |
| Estimation and Sampling of Unnormalized Statistical Models with Stein Score Matching J Liu, N Mehta, C Tao, L Carin | | |
