| 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 | 3283 | 2020 |
| H O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models Z Zhang, Y Sheng, T Zhou, T Chen, L Zheng, R Cai, Z Song, Y Tian, C Ré, ... Advances in Neural Information Processing Systems (NeurIPS), 2023 | 808 | 2023 |
| Graph Contrastive Learning Automated Y You, T Chen, Y Shen, Z Wang International Conference on Machine Learning (ICML), 2021 | 733 | 2021 |
| 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 | 721 | 2019 |
| Trustllm: Trustworthiness in large language models Y Huang, L Sun, H Wang, S Wu, Q Zhang, Y Li, C Gao, Y Huang, W Lyu, ... International Conference on Machine Learning (ICML Position Paper), 2024 | 643* | 2024 |
| 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 | 481 | 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 | 403 | 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 | 351 | 2023 |
| 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 | 333 | 2020 |
| When Does Self-Supervision Help Graph Convolutional Networks? Y You, T Chen, Z Wang, Y Shen International Conference on Machine Learning (ICML), 2020 | 308 | 2020 |
| Robust Pre-Training by Adversarial Contrastive Learning Z Jiang, T Chen, T Chen, Z Wang Advances in Neural Information Processing Systems (NeurIPS), 2020 | 307 | 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 | 299 | 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 | 259 | 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 | 255 | 2021 |
| 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 | 240 | 2022 |
| 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 | 175 | 2021 |
| 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 | 171 | 2022 |
| Unified Visual Transformer Compression S Yu, T Chen, J Shen, H Yuan, J Tan, S Yang, J Liu, Z Wang International Conference on Learning Representations (ICLR), 2021 | 169 | 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 | 160 | 2021 |
| 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 | 150* | 2023 |
Zhangyang (Atlas) WangXTX Markets & University of Texas at AustinVerified email at utexas.edu
