| Towards out-of-distribution generalization: A survey J Liu, Z Shen, Y He, X Zhang, R Xu, H Yu, P Cui arXiv preprint arXiv:2108.13624, 2021 | 418 | 2021 |
| Calibrated reliable regression using maximum mean discrepancy P Cui, W Hu, J Zhu Advances in Neural Information Processing Systems 33, 17164-17175, 2020 | 40 | 2020 |
| Neural eigenfunctions are structured representation learners Z Deng, J Shi, H Zhang, P Cui, C Lu, J Zhu arXiv preprint arXiv:2210.12637, 2022 | 10 | 2022 |
| Learning sample difficulty from pre-trained models for reliable prediction P Cui, D Zhang, Z Deng, Y Dong, J Zhu Advances in Neural Information Processing Systems 36, 2024 | 5 | 2024 |
| Confidence-based reliable learning under dual noises P Cui, Y Yue, Z Deng, J Zhu Advances in Neural Information Processing Systems 35, 35116-35129, 2022 | 3 | 2022 |
| Accurate and reliable forecasting using stochastic differential equations P Cui, Z Deng, W Hu, J Zhu arXiv preprint arXiv:2103.15041, 2021 | 2 | 2021 |
| Investigating uncertainty calibration of aligned language models under the multiple-choice setting G He, P Cui, J Chen, W Hu, J Zhu arXiv preprint arXiv:2310.11732, 2023 | 1 | 2023 |
| Towards Accelerated Model Training via Bayesian Data Selection Z Deng, P Cui, J Zhu Advances in Neural Information Processing Systems 36, 2024 | | 2024 |
| Deep Ensembles Meets Quantile Regression: Uncertainty-aware Imputation for Time Series Y Liu, P Cui, W Hu, R Hong arXiv preprint arXiv:2312.01294, 2023 | | 2023 |
| Heterogeneous multi-task Gaussian Cox processes F Zhou, Q Kong, Z Deng, F He, P Cui, J Zhu Machine Learning 112 (12), 5105-5134, 2023 | | 2023 |
