33 citations · 34 across the 2 of their papers we have counts for
2 papers
cs.LG2025★ 1 cited
Unifying Physics- and Data-Driven Modeling via Novel Causal Spatiotemporal Graph Neural Network for Interpretable Epidemic Forecasting
Shuai Han, Lukas Stelz, Thomas R. Sokolowski +2
Accurate epidemic forecasting is crucial for effective disease control and prevention. Traditional compartmental models often struggle to estimate temporally and spatially varying…
q-bio.QM2023★ 33 cited
Approaching epidemiological dynamics of COVID-19 with physics-informed neural networks
Shuai Han, Lukas Stelz, Horst Stoecker +2
A physics-informed neural network (PINN) embedded with the susceptible-infected-removed (SIR) model is devised to understand the temporal evolution dynamics of infectious diseases.…