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Physics-informedneural networks: Adeep learningframework for solvingforward and inverseproblems involvingnonlinear partialdifferentialequations Maziar RaissiParis PerdikarisGeorge Em Karniadakis2018 год

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
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Год издания: 2018
Авторы: Maziar Raissi, Paris Perdikaris, George Em Karniadakis
Издательство: Elsevier BV
Источник: Journal of Computational Physics
Ключевые слова: Model Reduction and Neural Networks, Fluid Dynamics and Turbulent Flows, Meteorological Phenomena and Simulations
Другие ссылки: Journal of Computational Physics (PDF)
Journal of Computational Physics (HTML)
OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (PDF)
OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (HTML)
OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (HTML)