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Jurnal
Journal of Scientific Computing
Scopus
ISSN 0885-7474 · Springer Science+Business Media · 2 artikel di indeks
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Artikel Jurnal Teks lengkap
Scientific Machine Learning Through Physics–Informed Neural Networks: Where we are and What’s Next
Abstract Physics-Informed Neural Networks (PINN) are neural networks (NNs) that encode model equations, like Partial Differential Equations (PDE), as a component of the neural network itself. PINNs are nowadays used to solve PDEs, fractional equations, integral-differential equations, and…
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Artikel Jurnal Teks lengkap
A Comprehensive Deep Learning-Based Approach to Reduced Order Modeling of Nonlinear Time-Dependent Parametrized PDEs
Abstract Conventional reduced order modeling techniques such as the reduced basis (RB) method (relying, e.g., on proper orthogonal decomposition (POD)) may incur in severe limitations when dealing with nonlinear time-dependent parametrized PDEs, as these are strongly anchored to the assumption of…