| SIR-Hawkes: Linking epidemic models and Hawkes processes to model diffusions in finite populations MA Rizoiu, S Mishra, Q Kong, M Carman, L Xie Proceedings of the 2018 world wide web conference, 419-428, 2018 | 185* | 2018 |
| Modeling information cascades with self-exciting processes via generalized epidemic models Q Kong, MA Rizoiu, L Xie proceedings of the 13th international conference on web search and data …, 2020 | 49 | 2020 |
| Will this video go viral: Explaining and predicting the popularity of youtube videos Q Kong, MA Rizoiu, S Wu, L Xie Companion Proceedings of the The Web Conference 2018, 175-178, 2018 | 46 | 2018 |
| Describing and predicting online items with reshare cascades via dual mixture self-exciting processes Q Kong, MA Rizoiu, L Xie Proceedings of the 29th ACM International Conference on Information …, 2020 | 29* | 2020 |
| Efficient inference for dynamic flexible interactions of neural populations F Zhou, Q Kong, Z Deng, J Kan, Y Zhang, C Feng, J Zhu Journal of Machine Learning Research 23 (211), 1-49, 2022 | 17* | 2022 |
| Slipping to the Extreme: A Mixed Method to Explain How Extreme Opinions Infiltrate Online Discussions Q Kong, E Booth, F Bailo, A Johns, MA Rizoiu Proceedings of the International AAAI Conference on Web and Social Media, 2022 | 16 | 2022 |
| Evently: Modeling and analyzing reshare cascades with hawkes processes Q Kong, R Ram, MA Rizoiu Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 16* | 2021 |
| Interval-censored transformer hawkes: Detecting information operations using the reaction of social systems Q Kong, P Calderon, R Ram, O Boichak, MA Rizoiu Proceedings of the ACM Web Conference 2023, 1813-1821, 2023 | 13 | 2023 |
| Birdspotter: A tool for analyzing and labeling twitter users R Ram, Q Kong, MA Rizoiu Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 11 | 2021 |
| pbmcapply: Tracking the Progress of Mc* pply with Progress Bar K Kuang, Q Kong, F Napolitano pbmcapply: Tracking the Progress of Mc* pply with Progress Bar, 2019 | 7 | 2019 |
| Linking epidemic models and hawkes point processes for modeling information diffusion Q Kong Proceedings of the Twelfth ACM International Conference on Web Search and …, 2019 | 6 | 2019 |
| Integration-free Training for Spatio-temporal Multimodal Covariate Deep Kernel Point Processes Y Zhang, Q Kong, F Zhou NeurIPS 2023, 2023 | 5 | 2023 |
| BioInformatics Agent (BIA): Unleashing the Power of Large Language Models to Reshape Bioinformatics Workflow Q Xin, Q Kong, H Ji, Y Shen, Y Liu, Y Sun, Z Zhang, Z Li, X Xia, B Deng, ... bioRxiv, 2024.05. 22.595240, 2024 | 3 | 2024 |
| Heterogeneous multi-task Gaussian Cox processes F Zhou, Q Kong, Z Deng, F He, P Cui, J Zhu Machine Learning 112 (12), 5105-5134, 2023 | 3 | 2023 |
| Contact tracing: Computational bounds, limitations and implications Q Kong, M Garcia-Herranz, I Dotu, M Cebrian arXiv preprint arXiv:2102.13349, 2021 | 3 | 2021 |
| Advances in Temporal Point Processes: Bayesian, Deep, and LLM Approaches F Zhou, Q Kong, Y Zhang arXiv preprint arXiv:2501.14291, 2025 | | 2025 |
| OTVIC: A Dataset with Online Transmission for Vehicle-to-Infrastructure Cooperative 3D Object Detection H Zhu, Y Wang, Q Kong, Y Wei, X Xia, B Deng, R Xiong, Y Wang 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2024 | | 2024 |
| Research and Implementation of Networked Cloud-Controlled Autonomous Driving System Y Wang, H Zhu, Q Kong, R Xiong, Y Wang 2024 43rd Chinese Control Conference (CCC), 6469-6476, 2024 | | 2024 |
| Enhancing Closed-Loop Performance in Learning-Based Vehicle Motion Planning by Integrating Rule-Based Insights Y Wang, Q Kong, H Zhu, D Zhang, L Lin, H Sha, X Xia, Q Liang, B Deng, ... IEEE Robotics and Automation Letters, 2024 | | 2024 |
| Linking Epidemic Models and Self-exciting Processes for Online and Offline Event Diffusions Q Kong PQDT-Global, 2022 | | 2022 |
Marian-Andrei RIZOIUUniversity of Technology SydneyEmail verificata su uts.edu.au