Thesis/thesis.bbl

\begin{thebibliography}{10}

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\newblock Auf dem Umschlag: Mit über 2,5 h Lösungsvideos zu ausgewählten
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\newblock Covasim: An agent-based model of covid-19 dynamics and interventions.
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\newblock Infectious disease models with time-varying parameters and general
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\newblock {\em Applied Mathematical Modelling}, 36(5):1974--1994, May 2012.

\bibitem{Maziarz2020}
M.~Maziarz and M.~Zach.
\newblock Agent‐based modelling for sars‐cov‐2 epidemic prediction and
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\newblock {\em Journal of Evaluation in Clinical Practice}, 26(5):1352--1360,
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C.~Millevoi, D.~Pasetto, and M.~Ferronato.
\newblock A physics-informed neural network approach for compartmental
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\newblock 2023.

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\bibitem{Moseley}
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\newblock So, what is a physics-informed neural network?
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\newblock {Accessed: 2024-09-08}.

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\newblock Description based on publisher supplied metadata and other sources.

\bibitem{Olumoyin2021}
K.~D. Olumoyin, A.~Q.~M. Khaliq, and K.~M. Furati.
\newblock Data-driven deep-learning algorithm for asymptomatic covid-19 model
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\newblock {\em Epidemiologia}, 2(4):471--489, Sept. 2021.

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\bibitem{Raissi2019}
M.~Raissi, P.~Perdikaris, and G.~Karniadakis.
\newblock Physics-informed neural networks: A deep learning framework for
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\newblock {\em Journal of Computational Physics}, 378:686--707, Feb. 2019.

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\newblock Covid-19-strategiepapiere und nationaler pandemieplan.
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\newblock {Accessed: 2024-09-06}.

\bibitem{GHDead}
RKI.
\newblock Github covid-19-todesfälle in deutschland.
\newblock
  \url{https://github.com/robert-koch-institut/COVID-19-Todesfaelle_in_Deutschland}.
\newblock {Accessed: 2024-09-05}.

\bibitem{GHInf}
RKI.
\newblock Github sars-cov-2 infektionen in deutschland.
\newblock
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\newblock {Accessed: 2024-09-05}.

\bibitem{RKIa}
RKI.
\newblock Sars-cov-2: Virologische basisdaten sowie virusvarianten im zeitraum
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\newblock
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\newblock {Accessed: 2024-09-05}.

\bibitem{Rosenblatt1958}
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W.~Rudin.
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\bibitem{Rumelhart1986}
D.~E. Rumelhart, G.~E. Hinton, and R.~J. Williams.
\newblock Learning representations by back-propagating errors.
\newblock {\em Nature}, 323(6088):533--536, Oct. 1986.

\bibitem{Setianto2023}
S.~Setianto and D.~Hidayat.
\newblock Modeling the time-dependent transmission rate using gaussian pulses
  for analyzing the covid-19 outbreaks in the world.
\newblock {\em Scientific Reports}, 13(1), Mar. 2023.

\bibitem{Shaier2021}
S.~Shaier, M.~Raissi, and P.~Seshaiyer.
\newblock Data-driven approaches for predicting spread of infectious diseases
  through dinns: Disease informed neural networks, 2021.

\bibitem{Smirnova2017}
A.~Smirnova, L.~deCamp, and G.~Chowell.
\newblock Forecasting epidemics through nonparametric estimation of
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\newblock {\em Bulletin of Mathematical Biology}, 81(11):4343--4365, May 2017.

\bibitem{SRD}
{Statista Research Department}.
\newblock Anzahl infektionen und todesfälle in zusammenhang mit dem
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\newblock {Accessed: 2024-09-06}.

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\bibitem{WHO}
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\newblock Coronavirus disease (covid-19).
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\end{thebibliography}