33 citations · 53 across the 5 of their papers we have counts for
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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…
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.…