33 citations · 53 across the 5 of their papers we have counts for
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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…
cs.LG2023★ 2 cited
Learning COVID-19 Regional Transmission Using Universal Differential Equations in a SIR model
Adrian Rojas-Campos, Lukas Stelz, Pascal Nieters
Highly-interconnected societies difficult to model the spread of infectious diseases such as COVID-19. Single-region SIR models fail to account for incoming forces of infection and…