| Dropedge: Towards deep graph convolutional networks on node classification Y Rong, W Huang, T Xu, J Huang arXiv preprint arXiv:1907.10903, 2019 | 812 | 2019 |
| Progressive feature alignment for unsupervised domain adaptation C Chen, W Xie, W Huang, Y Rong, X Ding, Y Huang, T Xu, J Huang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 316 | 2019 |
| Self-supervised graph transformer on large-scale molecular data Y Rong, Y Bian, T Xu, W Xie, Y Wei, W Huang, J Huang Advances in Neural Information Processing Systems 33, 12559-12571, 2020 | 284 | 2020 |
| Rumor detection on social media with bi-directional graph convolutional networks T Bian, X Xiao, T Xu, P Zhao, W Huang, Y Rong, J Huang Proceedings of the AAAI conference on artificial intelligence 34 (01), 549-556, 2020 | 282 | 2020 |
| Graph representation learning via graphical mutual information maximization Z Peng, W Huang, M Luo, Q Zheng, Y Rong, T Xu, J Huang Proceedings of The Web Conference 2020, 259-270, 2020 | 280 | 2020 |
| Deep multimodal fusion by channel exchanging Y Wang, W Huang, F Sun, T Xu, Y Rong, J Huang Advances in neural information processing systems 33, 4835-4845, 2020 | 119 | 2020 |
| MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm Q Bai, S Tan, T Xu, H Liu, J Huang, X Yao Briefings in bioinformatics 22 (3), bbaa161, 2021 | 114 | 2021 |
| A restricted black-box adversarial framework towards attacking graph embedding models H Chang, Y Rong, T Xu, W Huang, H Zhang, P Cui, W Zhu, J Huang Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3389-3396, 2020 | 97 | 2020 |
| Dtwnet: a dynamic time warping network X Cai, T Xu, J Yi, J Huang, S Rajasekaran Advances in neural information processing systems 32, 2019 | 58 | 2019 |
| Multi-view sparse co-clustering via proximal alternating linearized minimization J Sun, J Lu, T Xu, J Bi International Conference on Machine Learning, 757-766, 2015 | 54 | 2015 |
| Graph information bottleneck for subgraph recognition J Yu, T Xu, Y Rong, Y Bian, J Huang, R He arXiv preprint arXiv:2010.05563, 2020 | 53 | 2020 |
| Tackling over-smoothing for general graph convolutional networks W Huang, Y Rong, T Xu, F Sun, J Huang arXiv preprint arXiv:2008.09864, 2020 | 43 | 2020 |
| Spectral graph attention network H Chang, Y Rong, T Xu, W Huang, S Sojoudi, J Huang, W Zhu arXiv preprint arXiv:2003.07450, 2020 | 42* | 2020 |
| Generative models for De Novo drug design X Tong, X Liu, X Tan, X Li, J Jiang, Z Xiong, T Xu, H Jiang, N Qiao, ... Journal of Medicinal Chemistry 64 (19), 14011-14027, 2021 | 40 | 2021 |
| Multi-view graph neural networks for molecular property prediction H Ma, Y Bian, Y Rong, W Huang, T Xu, W Xie, G Ye, J Huang arXiv preprint arXiv:2005.13607, 2020 | 35* | 2020 |
| Molecular graph enhanced transformer for retrosynthesis prediction K Mao, X Xiao, T Xu, Y Rong, J Huang, P Zhao Neurocomputing 457, 193-202, 2021 | 31 | 2021 |
| The truly deep graph convolutional networks for node classification Y Rong, W Huang, T Xu, J Huang arXiv preprint arXiv:1907.10903 5, 2019 | 27 | 2019 |
| Application advances of deep learning methods for de novo drug design and molecular dynamics simulation Q Bai, S Liu, Y Tian, T Xu, AJ Banegas‐Luna, H Pérez‐Sánchez, J Huang, ... Wiley Interdisciplinary Reviews: Computational Molecular Science 12 (3), e1581, 2022 | 26 | 2022 |
| Re-balancing variational autoencoder loss for molecule sequence generation C Yan, S Wang, J Yang, T Xu, J Huang Proceedings of the 11th ACM International Conference on Bioinformatics …, 2020 | 25 | 2020 |
| Development and validation of an image-based deep learning algorithm for detection of synchronous peritoneal carcinomatosis in colorectal cancer Z Yuan, T Xu, J Cai, Y Zhao, W Cao, A Fichera, X Liu, J Yao, H Wang Annals of surgery 275 (4), e645-e651, 2022 | 23 | 2022 |
Junzhou Huang, FAIMBEJenkins Garrett Professor, Computer Science and Engineering, the University of Texas at ArlingtonVerified email at uta.edu
