| Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting Y Li, R Yu, C Shahabi, Y Liu ICLR, 2018 | 3695 | 2018 |
| Recurrent neural networks for multivariate time series with missing values Z Che, S Purushotham, K Cho, D Sontag, Y Liu Nature Scientific reports 8 (1), 6085, 2018 | 2215 | 2018 |
| Csi: A hybrid deep model for fake news detection N Ruchansky, S Seo, Y Liu Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017 | 1273 | 2017 |
| Spatiotemporal multi-graph convolution network for ride-hailing demand forecasting X Geng, Y Li, L Wang, L Zhang, Q Yang, J Ye, Y Liu 2019 AAAI Conference on Artificial Intelligence (AAAI’19), 2019 | 833 | 2019 |
| Adaptive gradient methods with dynamic bound of learning rate L Luo, Y Xiong, Y Liu, X Sun arXiv preprint arXiv:1902.09843, 2019 | 759 | 2019 |
| Combating fake news: A survey on identification and mitigation techniques K Sharma, F Qian, H Jiang, N Ruchansky, M Zhang, Y Liu ACM Transactions on Intelligent Systems and Technology (TIST) 10 (3), 21, 2019 | 588 | 2019 |
| The DARPA Twitter bot challenge VS Subrahmanian, A Azaria, S Durst, V Kagan, A Galstyan, K Lerman, ... Computer 49 (6), 38-46, 2016 | 562 | 2016 |
| Interpretable Convolutional Neural Networks with Dual Local and Global Attention for Review Rating Prediction S Seo, J Huang, H Yang, Y Liu Proceedings of the Eleventh ACM Conference on Recommender Systems, 297-305, 2017 | 547 | 2017 |
| Deep learning: A generic approach for extreme condition traffic forecasting R Yu, Y Li, C Shahabi, U Demiryurek, Y Liu Proceedings of the 2017 SIAM International Conference on Data Mining, 777-785, 2017 | 500 | 2017 |
| Benchmark of Deep Learning Models on Large Healthcare MIMIC Datasets S Purushotham, C Meng, Z Che, Y Liu Journal of biomedical informatics, 2018 | 483 | 2018 |
| Dyngem: Deep embedding method for dynamic graphs P Goyal, N Kamra, X He, Y Liu arXiv preprint arXiv:1805.11273, 2018 | 455 | 2018 |
| Topic-link LDA: joint models of topic and author community Y Liu, A Niculescu-Mizil, W Gryc proceedings of the 26th annual international conference on machine learning …, 2009 | 445 | 2009 |
| Temporal causal modeling with graphical granger methods A Arnold, Y Liu, N Abe Proceedings of the 13th ACM SIGKDD international conference on Knowledge …, 2007 | 392 | 2007 |
| Interpretable deep models for ICU outcome prediction Z Che, S Purushotham, R Khemani, Y Liu AMIA Annual Symposium Proceedings 2016, 371, 2016 | 365 | 2016 |
| Deep computational phenotyping Z Che, D Kale, W Li, MT Bahadori, Y Liu Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015 | 331 | 2015 |
| Text mining for product attribute extraction R Ghani, K Probst, Y Liu, M Krema, A Fano ACM SIGKDD Explorations Newsletter 8 (1), 41-48, 2006 | 309 | 2006 |
| Multi-task representation learning for travel time estimation Y Li, K Fu, Z Wang, C Shahabi, J Ye, Y Liu International Conference on Knowledge Discovery and Data Mining,(KDD), 2018 | 269 | 2018 |
| Neural User Response Generator: Fake News Detection with Collective User Intelligence YL Feng Qian, Chengyue Gong, Karishma Sharma IJCAI, 2018 | 243 | 2018 |
| Coronavirus on social media: Analyzing misinformation in Twitter conversations K Sharma, S Seo, C Meng, S Rambhatla, A Dua, Y Liu arXiv preprint arXiv:2003.12309, 2020 | 239 | 2020 |
| Collaborative topic regression with social matrix factorization for recommendation systems S Purushotham, Y Liu, CCJ Kuo arXiv preprint arXiv:1206.4684, 2012 | 236 | 2012 |
