| Out-of-distribution detection with deep nearest neighbors Y Sun, Y Ming, X Zhu, Y Li International Conference on Machine Learning, 20827-20840, 2022 | 414 | 2022 |
| React: Out-of-distribution detection with rectified activations Y Sun, C Guo, Y Li Advances in Neural Information Processing Systems 34, 144-157, 2021 | 413 | 2021 |
| Interpretable basis decomposition for visual explanation B Zhou, Y Sun, D Bau, A Torralba Proceedings of the European Conference on Computer Vision (ECCV), 119-134, 2018 | 348 | 2018 |
| Openood: Benchmarking generalized out-of-distribution detection J Yang, P Wang, D Zou, Z Zhou, K Ding, W Peng, H Wang, G Chen, B Li, ... Advances in Neural Information Processing Systems 35, 32598-32611, 2022 | 188 | 2022 |
| Dice: Leveraging sparsification for out-of-distribution detection Y Sun, Y Li European Conference on Computer Vision, 691-708, 2022 | 159 | 2022 |
| Revisiting the importance of individual units in cnns via ablation B Zhou, Y Sun, D Bau, A Torralba arXiv preprint arXiv:1806.02891, 2018 | 143 | 2018 |
| Delving into out-of-distribution detection with vision-language representations Y Ming, Z Cai, J Gu, Y Sun, W Li, Y Li Advances in neural information processing systems 35, 35087-35102, 2022 | 135 | 2022 |
| Cider: Exploiting hyperspherical embeddings for out-of-distribution detection Y Ming, Y Sun, O Dia, Y Li arXiv preprint arXiv:2203.04450 7 (10), 2022 | 119 | 2022 |
| Openood v1. 5: Enhanced benchmark for out-of-distribution detection J Zhang, J Yang, P Wang, H Wang, Y Lin, H Zhang, Y Sun, X Du, K Zhou, ... arXiv preprint arXiv:2306.09301, 2023 | 71 | 2023 |
| OpenCon: Open-world Contrastive Learning Y Sun, Y Li Transactions of Machine Learning Research, 2023 | 49 | 2023 |
| Rethinking domain generalization for face anti-spoofing: Separability and alignment Y Sun, Y Liu, X Liu, Y Li, WS Chu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 48 | 2023 |
| The Periodic Table of Data Structures S Idreos, K Zoumpatianos, M Athanassoulis, N Dayan, B Hentschel, ... IEEE Data Engineering Bulletin 41 (3), 64-75, 2018 | 45* | 2018 |
| Learning data structure alchemy S Idreos, K Zoumpatianos, S Chatterjee, W Qin, A Wasay, B Hentschel, ... Bulletin of the IEEE Computer Society Technical Committee on Data …, 2019 | 31* | 2019 |
| Dream the impossible: Outlier imagination with diffusion models X Du, Y Sun, J Zhu, Y Li Advances in Neural Information Processing Systems 36, 2024 | 28 | 2024 |
| Adaptive activation thresholding: Dynamic routing type behavior for interpretability in convolutional neural networks Y Sun, SN Ravi, V Singh Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 20 | 2019 |
| Faster R-CNN based autonomous navigation for vehicles in warehouse Y Sun, T Su, Z Tu 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM …, 2017 | 19 | 2017 |
| When and How Does Known Class Help Discover Unknown Ones? Provable Understanding Through Spectral Analysis Y Sun, Z Shi, Y Liang, Y Li International Conference on Machine Learning, 2023 | 18 | 2023 |
| A graph-theoretic framework for understanding open-world semi-supervised learning Y Sun, Z Shi, Y Li Advances in Neural Information Processing Systems 36, 2024 | 8 | 2024 |
| Uncertainty decomposition and quantification for in-context learning of large language models C Ling, X Zhao, W Cheng, Y Liu, Y Sun, X Zhang, M Oishi, T Osaki, ... arXiv preprint arXiv:2402.10189, 2024 | 5 | 2024 |
| How to Overcome Curse-of-Dimensionality for Out-of-Distribution Detection? SS Ghosal, Y Sun, Y Li Proceedings of the AAAI Conference on Artificial Intelligence 38 (18), 19849 …, 2024 | 4 | 2024 |
Sharon Yixuan LiUniversity of Wisconsin-MadisonПотвърден имейл адрес: cs.wisc.edu
