| Ood-bench: Benchmarking and understanding out-of-distribution generalization datasets and algorithms N Ye, K Li, L Hong, H Bai, Y Chen, F Zhou, Z Li arXiv preprint arXiv:2106.03721 1 (3), 5, 2021 | 58 | 2021 |
| Energy-based out-of-distribution detection for graph neural networks Q Wu, Y Chen, C Yang, J Yan The Eleventh International Conference on Learning Representations. (ICLR), 2023 | 41 | 2023 |
| Rethinking and improving robustness of convolutional neural networks: a shapley value-based approach in frequency domain Y Chen, Q Ren, J Yan Advances in Neural Information Processing Systems (NeurIPS) 35, 324-337, 2022 | 14 | 2022 |
| Towards a unified game-theoretic view of adversarial perturbations and robustness J Ren, D Zhang, Y Wang, L Chen, Z Zhou, Y Chen, X Cheng, X Wang, ... Advances in Neural Information Processing Systems 34, 3797-3810, 2021 | 11 | 2021 |
| Towards one-shot neural combinatorial solvers: Theoretical and empirical notes on the cardinality-constrained case R Wang, L Shen, Y Chen, X Yang, D Tao, J Yan The Eleventh International Conference on Learning Representations, 2022 | 10 | 2022 |
| Dice: Domain-attack invariant causal learning for improved data privacy protection and adversarial robustness Q Ren, Y Chen, Y Mo, Q Wu, J Yan Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 6 | 2022 |
| Going Beyond Neural Network Feature Similarity: The Network Feature Complexity and Its Interpretation Using Category Theory Y Chen, Z Zhou, J Yan The Twelfth International Conference on Learning Representations (ICLR 2024)., 2023 | 1 | 2023 |
