| Out-of-distribution detection with deep nearest neighbors Y Sun, Y Ming, X Zhu, Y Li ICML 2022, 2022 | 551 | 2022 |
| React: Out-of-distribution detection with rectified activations Y Sun, C Guo, Y Li NeurIPS 2021, 2021 | 514 | 2021 |
| Interpretable basis decomposition for visual explanation B Zhou*, Y Sun*, D Bau*, A Torralba ECCV 2018, 2018 | 367 | 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, ... NeurIPS 2022 (Benchmark Track), 2022 | 262 | 2022 |
| Dice: Leveraging sparsification for out-of-distribution detection Y Sun, Y Li ECCV 2022, 2022 | 208 | 2022 |
| Cider: Exploiting hyperspherical embeddings for out-of-distribution detection Y Ming, Y Sun, O Dia, Y Li ICLR 2022, 2022 | 172* | 2022 |
| Delving into out-of-distribution detection with vision-language representations Y Ming, Z Cai, J Gu, Y Sun, W Li, Y Li NeurIPS 2022, 2022 | 168 | 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 | 155 | 2018 |
| 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, ... DMLR 2024, 2023 | 128 | 2023 |
| Rethinking domain generalization for face anti-spoofing: Separability and alignment Y Sun, Y Liu, X Liu, Y Li, WS Chu CVPR 2023, 2023 | 72 | 2023 |
| OpenCon: Open-world Contrastive Learning Y Sun, Y Li TMLR 2023, 2023 | 63 | 2023 |
| Dream the impossible: Outlier imagination with diffusion models X Du, Y Sun, J Zhu, Y Li NeurIPS 2023, 2024 | 55 | 2024 |
| 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 | 47* | 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 |
| When and How Does Known Class Help Discover Unknown Ones? Provable Understanding Through Spectral Analysis Y Sun, Z Shi, Y Liang, Y Li ICML 2023, 2023 | 27 | 2023 |
| A graph-theoretic framework for understanding open-world semi-supervised learning Y Sun, Z Shi, Y Li NeurIPS 2023, 2024 | 23 | 2024 |
| Adaptive activation thresholding: Dynamic routing type behavior for interpretability in convolutional neural networks Y Sun, SN Ravi, V Singh ICCV 2019, 2019 | 23 | 2019 |
| Faster R-CNN based autonomous navigation for vehicles in warehouse Y Sun, T Su, Z Tu AIM 2017, 2017 | 20 | 2017 |
| 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, ... NAACL 2024 (long), 2024 | 14* | 2024 |
| How to Overcome Curse-of-Dimensionality for Out-of-Distribution Detection? SS Ghosal*, Y Sun*, Y Li AAAI 2024, 2024 | 11 | 2024 |
Sharon LiUniversity of Wisconsin-MadisonВерификована је имејл адреса на cs.wisc.edu