| 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 | 1778 | 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 | 589 | 2019 |
| Graph Contrastive Learning Automated Y You, T Chen, Y Shen, Z Wang International Conference on Machine Learning (ICML), 2021 | 411 | 2021 |
| 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 | 352 | 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 | 253 | 2020 |
| When Does Self-Supervision Help Graph Convolutional Networks? Y You, T Chen, Z Wang, Y Shen International Conference on Machine Learning (ICML), 2020 | 222 | 2020 |
| Robust Pre-Training by Adversarial Contrastive Learning Z Jiang, T Chen, T Chen, Z Wang Advances in Neural Information Processing Systems (NeurIPS), 2020 | 211 | 2020 |
| 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 | 187 | 2021 |
| 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 | 183 | 2021 |
| 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 | 168 | 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 | 160 | 2021 |
| More convnets in the 2020s: Scaling up kernels beyond 51x51 using sparsity S Liu, T Chen, X Chen, X Chen, Q Xiao, B Wu, M Pechenizkiy, D Mocanu, ... International Conference on Learning Representations (ICLR), 2023 | 130 | 2023 |
| Is Attention All NeRF Needs? M Varma T, P Wang, X Chen, T Chen, S Venugopalan, Z Wang International Conference on Learning Representations (ICLR), 2023 | 128* | 2023 |
| 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 | 124 | 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 | 109 | 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 | 94 | 2020 |
| 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 | 93 | 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 | 92 | 2020 |
| The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training S Liu, T Chen, X Chen, L Shen, DC Mocanu, Z Wang, M Pechenizkiy International Conference on Learning Representations (ICLR), 2022 | 89 | 2022 |
| Anti-Oversmoothing in Deep Vision Transformers via the Fourier Domain Analysis: From Theory to Practice P Wang, W Zheng, T Chen, Z Wang International Conference on Learning Representations (ICLR), 2022 | 88 | 2022 |
Zhangyang (Atlas) WangXTX Markets & University of Texas at Austin在 utexas.edu 的电子邮件经过验证
