| Fastgcn: fast learning with graph convolutional networks via importance sampling J Chen, T Ma, C Xiao ICLR2018, 2018 | 1316 | 2018 |
| Evolvegcn: Evolving graph convolutional networks for dynamic graphs A Pareja, G Domeniconi, J Chen, T Ma, T Suzumura, H Kanezashi, ... AAAI 2020, 2020 | 609 | 2020 |
| Constrained generation of semantically valid graphs via regularizing variational autoencoders T Ma, J Chen, C Xiao 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), 2018 | 199 | 2018 |
| Pre-training of graph augmented transformers for medication recommendation J Shang, T Ma, C Xiao, J Sun IJCAI 2019, 2019 | 157 | 2019 |
| Drug similarity integration through attentive multi-view graph auto-encoders T Ma, C Xiao, J Zhou, F Wang IJCAI'18: Proceedings of the 27th International Joint Conference on …, 2018 | 146 | 2018 |
| Gamenet: Graph augmented memory networks for recommending medication combination J Shang, C Xiao, T Ma, H Li, J Sun proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 1126-1133, 2019 | 137 | 2019 |
| Learning crosslingual word embeddings without bilingual corpora L Duong, H Kanayama, T Ma, S Bird, T Cohn arXiv preprint arXiv:1606.09403, 2016 | 132 | 2016 |
| Readmission prediction via deep contextual embedding of clinical concepts C Xiao, T Ma, AB Dieng, DM Blei, F Wang PloS one 13 (4), e0195024, 2018 | 111 | 2018 |
| Opinion target extraction in Chinese news comments T Ma, X Wan Coling 2010: Posters, 782-790, 2010 | 96 | 2010 |
| Health-atm: A deep architecture for multifaceted patient health record representation and risk prediction T Ma, C Xiao, F Wang Proceedings of the 2018 SIAM International Conference on Data Mining, 261-269, 2018 | 79 | 2018 |
| Pre-training BERT on domain resources for short answer grading C Sung, T Dhamecha, S Saha, T Ma, V Reddy, R Arora Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 76 | 2019 |
| Scalable graph learning for anti-money laundering: A first look M Weber, J Chen, T Suzumura, A Pareja, T Ma, H Kanezashi, T Kaler, ... arXiv preprint arXiv:1812.00076, 2018 | 76 | 2018 |
| MINA: multilevel knowledge-guided attention for modeling electrocardiography signals S Hong, C Xiao, T Ma, H Li, J Sun arXiv preprint arXiv:1905.11333, 2019 | 61 | 2019 |
| Multilingual training of crosslingual word embeddings L Duong, H Kanayama, T Ma, S Bird, T Cohn Proceedings of the 15th Conference of the European Chapter of the …, 2017 | 50 | 2017 |
| DeepDrawing: A Deep Learning Approach to Graph Drawing Y Wang, Z Jin, Q Wang, W Cui, T Ma, H Qu IEEE Transactions on Visualization and Computer Graphics 26 (1), 676-686, 2019 | 44 | 2019 |
| Deep Graph Matching and Searching for Semantic Code Retrieval X Ling, L Wu, S Wang, G Pan, T Ma, F Xu, AX Liu, C Wu, S Ji The ACM Transactions on Knowledge Discovery from Data (TKDD), 2021 | 42 | 2021 |
| Multilevel graph matching networks for deep graph similarity learning X Ling, L Wu, S Wang, T Ma, F Xu, AX Liu, C Wu, S Ji IEEE Transactions on Neural Networks and Learning Systems, 2021 | 36* | 2021 |
| Online Planner Selection with Graph Neural Networks and Adaptive Scheduling T Ma, P Ferber, S Huo, J Chen, M Katz AAAI 2020, 2020 | 35* | 2020 |
| Unsupervised Reference-Free Summary Quality Evaluation via Contrastive Learning H Wu, T Ma, L Wu, T Manyumwa, S Ji EMNLP 2020, 2020 | 33 | 2020 |
| Link prediction with persistent homology: An interactive view Z Yan, T Ma, L Gao, Z Tang, C Chen International Conference on Machine Learning, 11659-11669, 2021 | 27* | 2021 |
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