A physics-informed neural network to model COVID-19 infection and hospitalization scenarios.

Berkhahn S, Ehrhardt M

DOI: 10.1186/s13662-022-03733-5
Published: 2022
Container: Advances in continuous and discrete models
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1186/s13662-022-03733-5,
  title = {A physics-informed neural network to model COVID-19 infection and hospitalization scenarios.},
  author = {Berkhahn S and Ehrhardt M},
  year = {2022},
  journal = {Advances in continuous and discrete models},
  doi = {10.1186/s13662-022-03733-5},
  url = {https://doi.org/10.1186/s13662-022-03733-5}
}

RIS

TY  - JOUR
TI  - A physics-informed neural network to model COVID-19 infection and hospitalization scenarios.
AU  - Berkhahn S
AU  - Ehrhardt M
PY  - 2022
JO  - Advances in continuous and discrete models
DO  - 10.1186/s13662-022-03733-5
UR  - https://doi.org/10.1186/s13662-022-03733-5
ER  -

APA

S, B., & M, E. (2022). A physics-informed neural network to model COVID-19 infection and hospitalization scenarios.. Advances in continuous and discrete models. https://doi.org/10.1186/s13662-022-03733-5

Source records

pubmed · retrieved 2026-11-10T13:46:18.835Z