2 citations · 3 across the 6 of their papers we have counts for
7 papers
EpiQAL: Benchmarking Large Language Models in Epidemiological Question Answering and Reasoning
Mingyang Wei, Dehai Min, Zewen Liu +8
Reliable epidemiological reasoning requires synthesizing study evidence to infer disease burden, transmission dynamics, and intervention effects at the population level. Existing m…
Can Large Language Models Adequately Perform Symbolic Reasoning Over Time Series?
Zewen Liu, Juntong Ni, Xianfeng Tang +4
Uncovering hidden symbolic laws from time series data, as an aspiration dating back to Kepler's discovery of planetary motion, remains a core challenge in scientific discovery and…
Higher-order Interaction Matters: Dynamic Hypergraph Neural Networks for Epidemic Modeling
Songyuan Liu, Shengbo Gong, Tianning Feng +3
The ongoing need for effective epidemic modeling has driven advancements in capturing the complex dynamics of infectious diseases. Traditional models, such as Susceptible-Infected-…
Pre-training Epidemic Time Series Forecasters with Compartmental Prototypes
Zewen Liu, Juntong Ni, Bohan Wang +2
Accurate epidemic forecasting is crucial for outbreak preparedness, but existing data-driven models are often brittle. Typically trained on a single pathogen, they struggle with da…
Epidemiology-Aware Neural ODE with Continuous Disease Transmission Graph
Guancheng Wan, Zewen Liu, Max S. Y. Lau +2
Effective epidemic forecasting is critical for public health strategies and efficient medical resource allocation, especially in the face of rapidly spreading infectious diseases.…
EpiLearn: A Python Library for Machine Learning in Epidemic Modeling
Zewen Liu, Yunxiao Li, Mingyang Wei +3
EpiLearn is a Python toolkit developed for modeling, simulating, and analyzing epidemic data. Although there exist several packages that also deal with epidemic modeling, they are…
A Review of Graph Neural Networks in Epidemic Modeling
Zewen Liu, Guancheng Wan, B. Aditya Prakash +2
Since the onset of the COVID-19 pandemic, there has been a growing interest in studying epidemiological models. Traditional mechanistic models mathematically describe the transmiss…