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Generalization of Physics-Informed Neural Networks for Various Boundary and Initial Conditions

Schäfer, Violetta (2022) Generalization of Physics-Informed Neural Networks for Various Boundary and Initial Conditions. Master's, Technische Universität Kaiserslautern.

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Item URL in elib:https://elib.dlr.de/185457/
Document Type:Thesis (Master's)
Title:Generalization of Physics-Informed Neural Networks for Various Boundary and Initial Conditions
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Schäfer, ViolettaVioletta.Schaefer (at) dlr.deUNSPECIFIED
Date:11 January 2022
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Number of Pages:83
Status:Published
Keywords:Machine Learning Neuronale Netze Partielle Differentialgleichungen
Institution:Technische Universität Kaiserslautern
Department:Fachbereich Mathematik
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Tasks SISTEC
Location: Köln-Porz
Institutes and Institutions:Institute for Software Technology > High-Performance Computing
Institute for Software Technology
Deposited By: Schäfer, Violetta
Deposited On:02 Mar 2022 08:40
Last Modified:09 Mar 2022 15:28

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