| Dag-gnn: Dag structure learning with graph neural networks Y Yu, J Chen, T Gao, M Yu ICML arXiv preprint arXiv:1904.10098, 2019 | 167 | 2019 |
| Efficient Markov Blanket Discovery and Its Application T Gao, Q Ji IEEE Transactions on Cybernetics, 2016 | 47 | 2016 |
| Local causal discovery of direct causes and effects T Gao, Q Ji Advances in Neural Information Processing Systems 28, 2015 | 39 | 2015 |
| Generalized linear rule models D Wei, S Dash, T Gao, O Günlük ICML arXiv preprint arXiv:1906.01761, 2019 | 35 | 2019 |
| Proximal graphical event models D Bhattacharjya, D Subramanian, T Gao Advances in Neural Information Processing Systems 31, 2018 | 33 | 2018 |
| Local-to-global Bayesian network structure learning T Gao, K Fadnis, M Campbell International Conference on Machine Learning, 1193-1202, 2017 | 28 | 2017 |
| Efficient score-based Markov Blanket discovery T Gao, Q Ji International Journal of Approximate Reasoning 80, 277-293, 2017 | 25 | 2017 |
| Do multi-hop readers dream of reasoning chains? H Wang, M Yu, X Guo, R Das, W Xiong, T Gao arXiv preprint arXiv:1910.14520, 2019 | 23 | 2019 |
| Multi-step entity-centric information retrieval for multi-hop question answering R Das, A Godbole, D Kavarthapu, Z Gong, A Singhal, M Yu, X Guo, T Gao, ... Proceedings of the 2nd Workshop on Machine Reading for Question Answering …, 2019 | 22 | 2019 |
| Identifying the discourse function of news article paragraphs WV Yarlott, C Cornelio, T Gao, M Finlayson Proceedings of the Workshop Events and Stories in the News 2018, 25-33, 2018 | 20 | 2018 |
| Event-Driven Continuous Time Bayesian Networks D Bhattacharjya, K Shanmugam, T Gao, N Mattei, KR Varshney, ... AAAI, 2020 | 17 | 2020 |
| Parallel Bayesian network structure learning T Gao, D Wei International Conference on Machine Learning, 1685-1694, 2018 | 17 | 2018 |
| DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks D Wei, T Gao, Y Yu NeurIPS 20 arXiv preprint arXiv:2010.09133, 2020 | 14 | 2020 |
| Multi-step entity-centric information retrieval for multi-hop question answering A Godbole, D Kavarthapu, R Das, Z Gong, A Singhal, H Zamani, M Yu, ... arXiv preprint arXiv:1909.07598, 2019 | 14 | 2019 |
| Learning with Hidden Information Using a Max-Margin Latent Variable Model Z Wang, T Gao, Q Ji Proceedings of the 2014 22nd International Conference on Pattern Recognition …, 2014 | 14 | 2014 |
| Characterization of Overlap in Observational Studies M Oberst, FD Johansson, D Wei, T Gao, G Brat, D Sontag, KR Varshney AISTATS, 2020 | 11 | 2020 |
| Constrained Local Latent Variable Discovery. T Gao, Q Ji IJCAI, 1490-1496, 2016 | 9 | 2016 |
| DAGs with No Curl: An Efficient DAG Structure Learning Approach Y Yu, T Gao, N Yin, Q Ji ICML 21 arXiv preprint arXiv:2106.07197, 2021 | 7 | 2021 |
| Order-dependent event models for agent interactions D Bhattacharjya, T Gao, D Subramanian Proceedings of the Twenty-Ninth International Conference on International …, 2021 | 7 | 2021 |
| Pearl: Prototype learning via rule learning T Fu, T Gao, C Xiao, T Ma, J Sun Proceedings of the 10th ACM International Conference on Bioinformatics …, 2019 | 7 | 2019 |
Debarun BhattacharjyaResearcher, IBM T.J. Watson Research CenterVerified email at us.ibm.com
