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A Modified PINN Approach for Identifiable Compartmental Models in Epidemiology with Applications to COVID-19. (arXiv:2208.01169v1 [q-bio.PE])
Aug. 3, 2022, 1:11 a.m. | Haoran Hu, Connor M Kennedy, Panayotis G. Kevrekidis, Hongkun Zhang
stat.ML updates on arXiv.org arxiv.org
A variety of approaches using compartmental models have been used to study
the COVID-19 pandemic and the usage of machine learning methods with these
models has had particularly notable success. We present here an approach toward
analyzing accessible data on Covid-19's U.S. development using a variation of
the "Physics Informed Neural Networks" (PINN) which is capable of using the
knowledge of the model to aid learning. We illustrate the challenges of using
the standard PINN approach, then how with appropriate …
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