Conference Papers
(^ indicates equal contributions)
[In Submission] Juntong Ni, Zewen Liu, Shiyu Wang, Ming Jin, Wei Jin
TimeDistill: Efficient Long-term Time Series Forecasting with MLPs via Cross-Architecture Distillation [pdf][In Submission] Zewen Liu, Juntong Ni, Max S. Y. Lau, Wei Jin
CAPE: Covariate-Adjusted Pre-Training for Epidemic Forecasting [pdf][In Submission] Kun Guo^, Zewen Liu^, Zhiwei Chen, Haoteng Wen, Wei Jin, Jiliang Tang, Yi Chang
Learning on Graphs with Large Language Models (LLMs): A Deep Dive into Model Robustness [pdf][In Submission] Guancheng Wan, Zewen Liu, Max S. Y. Lau, B. Aditya Prakash, Wei Jin
Epidemiology-Aware Neural ODE with Continuous Disease Transmission Graph [pdf][08/2024] Zewen Liu, Yunxiao Li, Mingyang Wei, Guancheng Wan, Max S.Y. Lau, Wei Jin
EpiLearn: A Python Library for Machine Learning in Epidemic Modeling [pdf] [repo]
7th epiDAMIK ACM SIGKDD International Workshop on Epidemiology meets Data Mining and Knowledge Discover, 2024[08/2024] Zewen Liu^, Guancheng Wan^, B. Aditya Prakash, Max S. Y. Lau, Wei Jin
A Review of Graph Neural Networks in Epidemic Modeling [pdf] [reading list]
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2024
Journal Papers
(^ indicates equal contributions)
- [02/2024] Fei Li, Jiale Zhang, Kewei Li, Yu Peng, Haotian Zhang, Yiping Xu, Yue Yu, Yuteng Zhang, Zewen Liu, Ying Wang, Lan Huang, Fengfeng Zhou
GANSamples-ac4C: Enhancing ac4C site prediction via generative adversarial networks and transfer learning [pdf]
Analytical Biochemistry, 2024