| 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 | 620 | 2021 |
| Deep stable learning for out-of-distribution generalization X Zhang, P Cui, R Xu, L Zhou, Y He, Z Shen Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 328 | 2021 |
| Towards non-iid image classification: A dataset and baselines Y He, Z Shen, P Cui Pattern Recognition 110, 107383, 2021 | 212 | 2021 |
| Nico++: Towards better benchmarking for domain generalization X Zhang, Y He, R Xu, H Yu, Z Shen, P Cui arXiv preprint arXiv:2204.08040, 2022 | 93 | 2022 |
| Counterfactual prediction for bundle treatment H Zou, P Cui, B Li, Z Shen, J Ma, H Yang, Y He Advances in Neural Information Processing Systems 33, 19705-19715, 2020 | 62 | 2020 |
| Causpref: Causal preference learning for out-of-distribution recommendation Y He, Z Wang, P Cui, H Zou, Y Zhang, Q Cui, Y Jiang Proceedings of the ACM web conference 2022, 410-421, 2022 | 53 | 2022 |
| 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 | 50 | 2022 |
| Daring: Differentiable causal discovery with residual independence Y He, P Cui, Z Shen, R Xu, F Liu, Y Jiang Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 36 | 2021 |
| Progressive Generative Hashing for Image Retrieval. Y Ma, Y He, F Ding, S Hu, J Li, X Liu IJCAI, 871-877, 2018 | 23 | 2018 |
| Towards out-of-distribution generalization: A survey. arXiv 2021 Z Shen, J Liu, Y He, X Zhang, R Xu, H Yu, P Cui arXiv preprint arXiv:2108.13624, 0 | 21 | |
| Map: Towards balanced generalization of iid and ood through model-agnostic adapters M Zhang, J Yuan, Y He, W Li, Z Chen, K Kuang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 19 | 2023 |
| Stable learning via sparse variable independence H Yu, P Cui, Y He, Z Shen, Y Lin, R Xu, X Zhang Proceedings of the AAAI Conference on Artificial Intelligence 37 (9), 10998 …, 2023 | 14 | 2023 |
| Learning stable graphs from multiple environments with selection bias Y He, P Cui, J Ma, H Zou, X Wang, H Yang, PS Yu Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 13 | 2020 |
| Purify and generate: Learning faithful item-to-item graph from noisy user-item interaction behaviors Y He, Y Dong, P Cui, Y Jiao, X Wang, J Liu, PS Yu Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 9 | 2021 |
| Self-supervised deconfounding against spatio-temporal shifts: Theory and modeling J Ji, W Zhang, J Wang, Y He, C Huang arXiv preprint arXiv:2311.12472, 2023 | 7 | 2023 |
| Covariate-shift generalization via random sample weighting Y He, X Shen, R Xu, T Zhang, Y Jiang, W Zou, P Cui Proceedings of the AAAI Conference on Artificial Intelligence 37 (10), 11828 …, 2023 | 6 | 2023 |
| Full bayesian significance testing for neural networks Z Liu, Z Li, J Wang, Y He Proceedings of the AAAI Conference on Artificial Intelligence 38 (8), 8841-8849, 2024 | 5 | 2024 |
| Rethinking the evaluation protocol of domain generalization H Yu, X Zhang, R Xu, J Liu, Y He, P Cui Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 5 | 2024 |
| Nico challenge: Out-of-distribution generalization for image recognition challenges X Zhang, Y He, T Wang, J Qi, H Yu, Z Wang, J Peng, R Xu, Z Shen, Y Niu, ... European Conference on Computer Vision, 433-450, 2022 | 5 | 2022 |
| Full Bayesian significance testing for neural networks in traffic forecasting Z Liu, J Wang, Z Li, Y He Proceedings of the Thirty-Third International Joint Conference on Artificial …, 2024 | 4 | 2024 |
