| Deep irregular convolutional residual LSTM for urban traffic passenger flows prediction B Du, H Peng, S Wang, MZA Bhuiyan, L Wang, Q Gong, L Liu, J Li IEEE Transactions on Intelligent Transportation Systems 21 (3), 972-985, 2019 | 107 | 2019 |
| S-net: From answer extraction to answer generation for machine reading comprehension C Tan, F Wei, N Yang, B Du, W Lv, M Zhou arXiv preprint arXiv:1706.04815, 2017 | 72 | 2017 |
| Parallel architecture of convolutional bi-directional LSTM neural networks for network-wide metro ridership prediction X Ma, J Zhang, B Du, C Ding, L Sun IEEE Transactions on Intelligent Transportation Systems 20 (6), 2278-2288, 2018 | 71 | 2018 |
| Dynamic pricing in spatial crowdsourcing: A matching-based approach Y Tong, L Wang, Z Zhou, L Chen, B Du, J Ye Proceedings of the 2018 International Conference on Management of Data, 773-788, 2018 | 64 | 2018 |
| Structure sensitive hashing with adaptive product quantization X Liu, B Du, C Deng, M Liu, B Lang IEEE transactions on cybernetics 46 (10), 2252-2264, 2015 | 64 | 2015 |
| Spatial temporal incidence dynamic graph neural networks for traffic flow forecasting H Peng, H Wang, B Du, MZA Bhuiyan, H Ma, J Liu, L Wang, Z Yang, L Du, ... Information Sciences 521, 277-290, 2020 | 61 | 2020 |
| Catch me if you can: Detecting pickpocket suspects from large-scale transit records B Du, C Liu, W Zhou, Z Hou, H Xiong Proceedings of the 22nd ACM SIGKDD international conference on knowledge …, 2016 | 60 | 2016 |
| Co-prediction of multiple transportation demands based on deep spatio-temporal neural network J Ye, L Sun, B Du, Y Fu, X Tong, H Xiong Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 43 | 2019 |
| Attentive crowd flow machines L Liu, R Zhang, J Peng, G Li, B Du, L Lin Proceedings of the 26th ACM international conference on Multimedia, 1553-1561, 2018 | 39 | 2018 |
| S-net: From answer extraction to answer synthesis for machine reading comprehension C Tan, F Wei, N Yang, B Du, W Lv, M Zhou Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 39 | 2018 |
| Estimation of missing values in heterogeneous traffic data: Application of multimodal deep learning model L Li, B Du, Y Wang, L Qin, H Tan Knowledge-Based Systems 194, 105592, 2020 | 32 | 2020 |
| Dynamic spatial-temporal representation learning for traffic flow prediction L Liu, J Zhen, G Li, G Zhan, Z He, B Du, L Lin IEEE Transactions on Intelligent Transportation Systems, 2020 | 30 | 2020 |
| Demand-aware charger planning for electric vehicle sharing B Du, Y Tong, Z Zhou, Q Tao, W Zhou Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 27 | 2018 |
| Context-aware answer sentence selection with hierarchical gated recurrent neural networks C Tan, F Wei, Q Zhou, N Yang, B Du, W Lv, M Zhou IEEE/ACM Transactions on Audio, Speech, and Language Processing 26 (3), 540-549, 2017 | 25 | 2017 |
| Graph CNNs for urban traffic passenger flows prediction J Li, H Peng, L Liu, G Xiong, B Du, H Ma, L Wang, MZA Bhuiyan 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced …, 2018 | 24 | 2018 |
| Multiple relational attention network for multi-task learning J Zhao, B Du, L Sun, F Zhuang, W Lv, H Xiong Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 23 | 2019 |
| KID model-driven things-edge-cloud computing paradigm for traffic data as a service B Du, R Huang, Z Xie, J Ma, W Lv IEEE Network 32 (1), 34-41, 2018 | 23 | 2018 |
| Traffic demand prediction based on dynamic transition convolutional neural network B Du, X Hu, L Sun, J Liu, Y Qiao, W Lv IEEE Transactions on Intelligent Transportation Systems 22 (2), 1237-1247, 2020 | 22 | 2020 |
| LSTM variants meet graph neural networks for road speed prediction Z Lu, W Lv, Y Cao, Z Xie, H Peng, B Du Neurocomputing 400, 34-45, 2020 | 18 | 2020 |
| Deep spatio-temporal graph convolutional network for traffic accident prediction L Yu, B Du, X Hu, L Sun, L Han, W Lv Neurocomputing 423, 135-147, 2021 | 17 | 2021 |
