Ood-bench: Quantifying and understanding two dimensions of out-of-distribution generalization N Ye, K Li, H Bai, R Yu, L Hong, F Zhou, Z Li, J Zhu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 81 | 2022 |
Slimmable dataset condensation S Liu, J Ye, R Yu, X Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 54 | 2023 |
Distribution Shift Inversion for Out-of-Distribution Prediction R Yu, S Liu, X Yang, X Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 13 | 2023 |
Kan or mlp: A fairer comparison R Yu, W Yu, X Wang arXiv preprint arXiv:2407.16674, 2024 | 7 | 2024 |
Regularization Penalty Optimization for Addressing Data Quality Variance in OoD Algorithms R Yu, H Zhu, K Li, L Hong, R Zhang, N Ye, SL Huang, X He Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8945-8953, 2022 | 4 | 2022 |
Generator Born from Classifier R Yu, X Wang Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
Encapsulating Knowledge in One Prompt Q Li, R Yu, X Wang arXiv preprint arXiv:2407.11902, 2024 | | 2024 |
Through the Dual-Prism: A Spectral Perspective on Graph Data Augmentation for Graph Classification Y Xia, R Yu, Y Liang, X Bresson, X Wang, R Zimmermann arXiv preprint arXiv:2401.09953, 2024 | | 2024 |
Neural Lineage R Yu, X Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | | 2024 |
Robust Long-Tailed Learning via Label-Aware Bounded CVaR H Zhu, R Yu, X Tang, Y Wang, Y Fang, Y Wang arXiv preprint arXiv:2308.15405, 2023 | | 2023 |