| Graph Contrastive Learning with Augmentations Y You, T Chen, Y Sui, T Chen, Z Wang, Y Shen Advances in Neural Information Processing Systems (NeurIPS), 2020 | 642 | 2020 |
| Abd-net: Attentive but diverse person re-identification T Chen, S Ding, J Xie, Y Yuan, W Chen, Y Yang, Z Ren, Z Wang IEEE International Conference on Computer Vision (ICCV), 2019 | 389 | 2019 |
| The Lottery Ticket Hypothesis for Pre-trained BERT Networks T Chen, J Frankle, S Chang, S Liu, Y Zhang, Z Wang, M Carbin Advances in Neural Information Processing Systems (NeurIPS), 2020 | 176 | 2020 |
| Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning T Chen, S Liu, S Chang, Y Cheng, L Amini, Z Wang IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020 | 166 | 2020 |
| When Does Self-Supervision Help Graph Convolutional Networks? Y You, T Chen, Z Wang, Y Shen International Conference on Machine Learning (ICML), 2020 | 139 | 2020 |
| Graph Contrastive Learning Automated Y You, T Chen, Y Shen, Z Wang International Conference on Machine Learning (ICML), 2021 | 134 | 2021 |
| Robust Pre-Training by Adversarial Contrastive Learning Z Jiang, T Chen, T Chen, Z Wang Advances in Neural Information Processing Systems (NeurIPS), 2020 | 110 | 2020 |
| Robust overfitting may be mitigated by properly learned smoothening T Chen, Z Zhang, S Liu, S Chang, Z Wang International Conference on Learning Representation (ICLR), 2021 | 90 | 2021 |
| The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models T Chen, J Frankle, S Chang, S Liu, Y Zhang, M Carbin, Z Wang IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021 | 70 | 2021 |
| Learning to optimize: A primer and a benchmark T Chen, X Chen, W Chen, H Heaton, J Liu, Z Wang, W Yin Journal of Machine Learning Research (JMLR), 2021 | 64 | 2021 |
| Triple wins: Boosting accuracy, robustness and efficiency together by enabling input-adaptive inference TK Hu, T Chen, H Wang, Z Wang International Conference on Learning Representation (ICLR), 2020 | 64 | 2020 |
| Chasing Sparsity in Vision Transformers: An End-to-End Exploration T Chen, Y Cheng, Z Gan, L Yuan, L Zhang, Z Wang Advances in Neural Information Processing Systems (NeurIPS), 2021 | 61 | 2021 |
| A Unified Lottery Ticket Hypothesis for Graph Neural Networks T Chen, Y Sui, X Chen, A Zhang, Z Wang International Conference on Machine Learning (ICML), 2021 | 61 | 2021 |
| Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training X Chen, W Chen, T Chen, Y Yuan, C Gong, K Chen, Z Wang International Conference on Machine Learning (ICML), 2020 | 49 | 2020 |
| L^ 2-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks Y You, T Chen, Z Wang, Y Shen IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020 | 47 | 2020 |
| Once-for-all adversarial training: In-situ tradeoff between robustness and accuracy for free ZW Wang, Haotao, Chen, Tianlong, Shupeng Gui, Ting-Kuei Hu, Ji Liu Advances in Neural Information Processing Systems (NeurIPS), 2020 | 45* | 2020 |
| LONG LIVE THE LOTTERY: THE EXISTENCE OF WIN-NING TICKETS IN LIFELONG LEARNING T Chen, Z Zhang, S Liu, S Chang, Z Wang International Conference on Learning Representation (ICLR), 2021 | 43 | 2021 |
| Data-Efficient GAN Training Beyond (Just) Augmentations: A Lottery Ticket Perspective T Chen, Y Cheng, Z Gan, J Liu, Z Wang Advances in Neural Information Processing Systems (NeurIPS), 2021 | 40* | 2021 |
| Sparse Training via Boosting Pruning Plasticity with Neuroregeneration S Liu, T Chen, X Chen, Z Atashgahi, L Yin, H Kou, L Shen, M Pechenizkiy, ... Advances in Neural Information Processing Systems (NeurIPS), 2021 | 38 | 2021 |
| Learning to Optimize in Swarms Y Cao, T Chen, Z Wang, Y Shen Advances in Neural Information Processing Systems (NeurIPS), 2019 | 38 | 2019 |
Zhangyang (Atlas) WangUniversity of Texas at Austin & Picsart AI ResearchVerified email at utexas.edu
