| Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting Y Li, R Yu, C Shahabi, Y Liu ICLR, 2018 | 1289 | 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 | 1235 | 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 | 729 | 2017 |
| Adaptive gradient methods with dynamic bound of learning rate L Luo, Y Xiong, Y Liu, X Sun arXiv preprint arXiv:1902.09843, 2019 | 434 | 2019 |
| The DARPA Twitter bot challenge VS Subrahmanian, A Azaria, S Durst, V Kagan, A Galstyan, K Lerman, ... Computer 49 (6), 38-46, 2016 | 422 | 2016 |
| 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 | 405 | 2009 |
| 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 | 378 | 2019 |
| 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 | 345 | 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 | 332 | 2017 |
| Temporal causal modeling with graphical granger methods A Arnold, Y Liu, N Abe Proceedings of the 13th ACM SIGKDD international conference on Knowledge …, 2007 | 324 | 2007 |
| 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 | 278 | 2019 |
| Benchmark of Deep Learning Models on Large Healthcare MIMIC Datasets S Purushotham, C Meng, Z Che, Y Liu Journal of biomedical informatics, 2018 | 274 | 2018 |
| Deep computational phenotyping Z Che, D Kale, W Li, MT Bahadori, Y Liu Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015 | 266 | 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 | 265 | 2006 |
| Interpretable deep models for ICU outcome prediction Z Che, S Purushotham, R Khemani, Y Liu AMIA Annual Symposium Proceedings 2016, 371, 2016 | 243 | 2016 |
| Dyngem: Deep embedding method for dynamic graphs P Goyal, N Kamra, X He, Y Liu arXiv preprint arXiv:1805.11273, 2018 | 232 | 2018 |
| Collaborative topic regression with social matrix factorization for recommendation systems S Purushotham, Y Liu, CCJ Kuo arXiv preprint arXiv:1206.4684, 2012 | 223 | 2012 |
| Kernel conditional random fields: representation and clique selection J Lafferty, X Zhu, Y Liu Proceedings of the twenty-first international conference on Machine learning, 64, 2004 | 210 | 2004 |
| On predicting rare classes with SVM ensembles in scene classification R Yan, Y Liu, R Jin, A Hauptmann Acoustics, Speech, and Signal Processing, 2003. Proceedings.(ICASSP'03 …, 2003 | 208 | 2003 |
| Grouped graphical Granger modeling for gene expression regulatory networks discovery AC Lozano, N Abe, Y Liu, S Rosset Bioinformatics 25 (12), i110-i118, 2009 | 176 | 2009 |
