| Stacked Generative Adversarial Networks X Huang, Y Li, O Poursaeed, J Hopcroft, S Belongie IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 | 2630* | 2017 |
| Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks S Liang, Y Li, R Srikant International Conference on Learning Representation (ICLR'18), 2018 | 977 | 2018 |
| Exploring the limits of weakly supervised pretraining D Mahajan, R Girshick, V Ramanathan, K He, M Paluri, Y Li, A Bharambe, ... Proceedings of the European conference on computer vision (ECCV), 181-196, 2018 | 942 | 2018 |
| Snapshot Ensembles: Train 1, Get M for Free G Huang*, Y Li*, G Pleiss, Z Liu, JE Hopcroft, KQ Weinberger International Conference on Learning Representation (ICLR 2017), 2017 | 644 | 2017 |
| Convergent Learning: Do different neural networks learn the same representations? Y Li, J Yosinski, J Clune, H Lipson, J Hopcroft International Conference on Learning Representation (ICLR'16), 2015 | 219 | 2015 |
| Energy-based Out-of-distribution Detection W Liu, X Wang, J Owens, Y Li Advances in Neural Information Processing Systems 33, 2020 | 176 | 2020 |
| Uncovering the small community structure in large networks: A local spectral approach Y Li, K He, D Bindel, JE Hopcroft Proceedings of the 24th international conference on world wide web, 658-668, 2015 | 119 | 2015 |
| The lifecycle and cascade of wechat social messaging groups J Qiu, Y Li, J Tang, Z Lu, H Ye, B Chen, Q Yang, JE Hopcroft Proceedings of the 25th International Conference on World Wide Web, 311-320, 2016 | 84 | 2016 |
| Local spectral clustering for overlapping community detection Y Li, K He, K Kloster, D Bindel, J Hopcroft ACM Transactions on Knowledge Discovery from Data (TKDD) 12 (2), 1-27, 2018 | 73* | 2018 |
| Deep manifold traversal: Changing labels with convolutional features JR Gardner, P Upchurch, MJ Kusner, Y Li, KQ Weinberger, K Bala, ... arXiv preprint arXiv:1511.06421, 2015 | 73 | 2015 |
| Understanding the loss surface of neural networks for binary classification S Liang, R Sun, Y Li, R Srikant International Conference on Machine Learning (ICML), 2835-2843, 2018 | 66 | 2018 |
| Detecting overlapping communities from local spectral subspaces K He, Y Sun, D Bindel, J Hopcroft, Y Li 2015 IEEE international conference on data mining, 769-774, 2015 | 64 | 2015 |
| Generalized out-of-distribution detection: A survey J Yang, K Zhou, Y Li, Z Liu arXiv preprint arXiv:2110.11334, 2021 | 48 | 2021 |
| Defense against adversarial images using web-scale nearest-neighbor search A Dubey, L Maaten, Z Yalniz, Y Li, D Mahajan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 47 | 2019 |
| In a world that counts: Clustering and detecting fake social engagement at scale Y Li, O Martinez, X Chen, Y Li, JE Hopcroft Proceedings of the 25th International Conference on World Wide Web, 111-120, 2016 | 43 | 2016 |
| Robust Out-of-distribution Detection in Neural Networks J Chen, Y Li, X Wu, Y Liang, S Jha arXiv preprint arXiv:2003.09711, 2020 | 38 | 2020 |
| Model Patching: Closing the Subgroup Performance Gap with Data Augmentation K Goel, A Gu, Y Li, C Ré International Conference on Learning Representation (ICLR), 2021 | 37 | 2021 |
| Towards Measuring and Inferring User Interest From Gaze Y Li, P Xu, D Lagun, V Navalpakkam Proceedings of 26th International Conference on World Wide Web (WWW'17), 2017 | 35 | 2017 |
| MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space R Huang, Y Li Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 24 | 2021 |
| MOOD: Multi-level Out-of-distribution Detection Z Lin, SD Roy, Y Li Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 23 | 2021 |
John HopcroftCornell UniversityVerified email at cs.cornell.edu
