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Approaching epidemiological dynamics of COVID-19 with physics-informed
  neural networks

Approaching epidemiological dynamics of COVID-19 with physics-informed neural networks

17 February 2023
Shuai Han
Lukas Stelz
Horst Stoecker
L. Wang
Kai Zhou
    AI4CE
    PINN
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Papers citing "Approaching epidemiological dynamics of COVID-19 with physics-informed neural networks"

3 / 3 papers shown
Title
Unifying Physics- and Data-Driven Modeling via Novel Causal Spatiotemporal Graph Neural Network for Interpretable Epidemic Forecasting
Unifying Physics- and Data-Driven Modeling via Novel Causal Spatiotemporal Graph Neural Network for Interpretable Epidemic Forecasting
Shuai Han
Lukas Stelz
Thomas R. Sokolowski
K. Zhou
H. Stocker
23
0
0
07 Apr 2025
A data augmentation strategy for deep neural networks with application to epidemic modelling
A data augmentation strategy for deep neural networks with application to epidemic modelling
Muhammad Awais
Abu Sayfan Ali
Giacomo Dimarco
Federica Ferrarese
Lorenzo Pareschi
27
0
0
28 Feb 2025
COVID-19 Modeling: A Review
COVID-19 Modeling: A Review
LongBing Cao
Qing Liu
40
44
0
16 Apr 2021
1