| 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, 2023 | 410 | 2023 |
| Heterogeneous risk minimization J Liu, Z Hu, P Cui, B Li, Z Shen International Conference on Machine Learning, 6804-6814, 2021 | 109 | 2021 |
| Stable learning via differentiated variable decorrelation Z Shen, P Cui, J Liu, T Zhang, B Li, Z Chen Proceedings of the 26th acm sigkdd international conference on knowledge …, 2020 | 45 | 2020 |
| Triple generative adversarial networks C Li, K Xu, J Zhu, J Liu, B Zhang IEEE transactions on pattern analysis and machine intelligence 44 (12), 9629 …, 2021 | 29 | 2021 |
| Invariant preference learning for general debiasing in recommendation Z Wang, Y He, J Liu, W Zou, PS Yu, P Cui Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 28 | 2022 |
| Kernelized heterogeneous risk minimization J Liu, Z Hu, P Cui, B Li, Z Shen arXiv preprint arXiv:2110.12425, 2021 | 28* | 2021 |
| Stable adversarial learning under distributional shifts J Liu, Z Shen, P Cui, L Zhou, K Kuang, B Li, Y Lin Proceedings of the AAAI Conference on Artificial Intelligence 35 (10), 8662-8670, 2021 | 24 | 2021 |
| Signed graph neural network with latent groups H Liu, Z Zhang, P Cui, Y Zhang, Q Cui, J Liu, W Zhu Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 22 | 2021 |
| Towards domain generalization in object detection X Zhang, Z Xu, R Xu, J Liu, P Cui, W Wan, C Sun, C Li arXiv preprint arXiv:2203.14387, 2022 | 21 | 2022 |
| Distributionally robust learning with stable adversarial training J Liu, Z Shen, P Cui, L Zhou, K Kuang, B Li IEEE Transactions on Knowledge and Data Engineering, 2022 | 14 | 2022 |
| Distributionally robust optimization with data geometry J Liu, J Wu, B Li, P Cui Advances in neural information processing systems 35, 33689-33701, 2022 | 9 | 2022 |
| On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets J Liu, T Wang, P Cui, H Namkoong NeurIPS 2023, Dataset and Benchmark Track, 2023 | 6 | 2023 |
| Towards the ultimate PMT waveform analysis for neutrino and dark matter experiments DC Xu, BD Xu, EJ Bao, YY Wu, AQ Zhang, YY Wang, GL Zhang, Y Xu, ... Journal of Instrumentation 17 (06), P06040, 2022 | 6 | 2022 |
| Bridging the gap: neural collapse inspired prompt tuning for generalization under class imbalance D Zhu, Y Li, M Zhang, J Yuan, J Liu, K Kuang, C Wu arXiv preprint arXiv:2306.15955, 2023 | 4 | 2023 |
| Measure the Predictive Heterogeneity J Liu, J Wu, R Pi, R Xu, X Zhang, B Li, P Cui The Eleventh International Conference on Learning Representations, 2023 | 3 | 2023 |
| Enhancing Distributional Stability among Sub-populations J Liu, J Wu, J Peng, X Wu, Y Zheng, B Li, P Cui International Conference on Artificial Intelligence and Statistics (AISTATS …, 2024 | 2* | 2024 |
| Meta Adaptive Task Sampling for Few-Domain Generalization Z Shen, H Yu, P Cui, J Liu, X Zhang, L Zhou, F Liu arXiv preprint arXiv:2305.15644, 2023 | 1 | 2023 |
| Rethinking the Evaluation Protocol of Domain Generalization H Yu, X Zhang, R Xu, J Liu, Y He, P Cui arXiv preprint arXiv:2305.15253, 2023 | 1 | 2023 |
| Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications J Liu, J Wu, T Wang, H Zou, B Li, P Cui arXiv preprint arXiv:2311.05054, 2023 | | 2023 |
| Exploring and Exploiting Data Heterogeneity in Recommendation Z Wang, J Liu, H Zou, X Zhang, Y He, D Liang, P Cui arXiv preprint arXiv:2305.15431, 2023 | | 2023 |
Peng CuiDepartment of Computer Science, Tsinghua UniversityVerified email at tsinghua.edu.cn
