| Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data YC Hsu, Y Shen, H Jin, Z Kira CVPR, 2020 | 580 | 2020 |
| Re-evaluating Continual Learning Scenarios: A Categorization and Case for Strong Baselines YC Hsu, YC Liu, A Ramasamy, Z Kira NeurIPS Continual Learning Workshop, 2018 | 371 | 2018 |
| Learning to cluster in order to Transfer across domains and tasks YC Hsu, Z Lv, Z Kira International Conference on Learning Representations (ICLR), 2018 | 234 | 2018 |
| Multi-class Classification without Multi-class Labels YC Hsu, Z Lv, J Schlosser, P Odom, Z Kira International Conference on Learning Representations (ICLR), 2019 | 181 | 2019 |
| Training Student Networks for Acceleration with Conditional Adversarial Networks Z Xu, YC Hsu, J Huang British Machine Vision Conference (BMVC), 2018 | 169* | 2018 |
| Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning J Smith, YC Hsu, J Balloch, Y Shen, H Jin, Z Kira ICCV 2021, 2021 | 167 | 2021 |
| Neural network-based clustering using pairwise constraints YC Hsu, Z Kira International Conference on Learning Representations (ICLR) Workshop Track, 2016 | 94 | 2016 |
| Posterior Re-calibration for Imbalanced Datasets J Tian, YC Liu, N Glaser, YC Hsu, Z Kira NeurIPS 2020, 2020 | 72 | 2020 |
| Learning to Cluster for Proposal-Free Instance Segmentation YC Hsu, Z Xu, Z Kira, J Huang International Joint Conference on Neural Networks (IJCNN), 2018 | 68 | 2018 |
| Language model compression with weighted low-rank factorization YC Hsu, T Hua, S Chang, Q Lou, Y Shen, H Jin International Conference on Learning Representations (ICLR), 2022 | 55 | 2022 |
| A closer look at rehearsal-free continual learning JS Smith, J Tian, S Halbe, YC Hsu, Z Kira Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 41 | 2023 |
| Enhancing the Generalization for Intent Classification and Out-of-Domain Detection in SLU Y Shen, YC Hsu, A Ray, H Jin ACL, 2021 | 35 | 2021 |
| Memory-Efficient Semi-Supervised Continual Learning: The World is its Own Replay Buffer J Smith, J Balloch, YC Hsu, Z Kira International Joint Conference on Neural Networks (IJCNN), 2021 | 35 | 2021 |
| A geometric perspective towards neural calibration via sensitivity decomposition J Tian, D Yung, YC Hsu, Z Kira NeurIPS 2021 Spotlights (top 3%), 2021 | 26 | 2021 |
| Spectrofluorometric assay for monoamine-preferring phenol sulfotransferase (SULT1A3) LY Lu, YC Hsu, YS Yang Analytical biochemistry 404 (2), 241-243, 2010 | 21 | 2010 |
| Deep Image Category Discovery using a Transferred Similarity Function YC Hsu, Z Lv, Z Kira arXiv preprint arXiv:1612.01253, 2016 | 16 | 2016 |
| Token Fusion: Bridging the Gap between Token Pruning and Token Merging M Kim, S Gao, YC Hsu, Y Shen, H Jin WACV, 2023 | 10 | 2023 |
| Numerical Optimizations for Weighted Low-rank Estimation on Language Models T Hua, YC Hsu, F Wang, Q Lou, Y Shen, H Jin EMNLP, 2022 | 10 | 2022 |
| Exploring Covariate and Concept Shift for Out-of-Distribution Detection J Tian, YC Hsu, Y Shen, H Jin, Z Kira NeurIPS 2021 Workshop on Distribution Shifts: Connecting Methods and …, 2021 | 9* | 2021 |
| A Closer Look at Knowledge Distillation with Features, Logits, and Gradients YC Hsu, J Smith, Y Shen, Z Kira, H Jin | 7 | 2022 |
Zsolt KiraAssistant Professor, Georgia Institute of Technology在 gatech.edu 的电子邮件经过验证
