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Deep Learning-Based Forward Modeling and Inversion Techniques for Computational Physics Problems

Deep Learning-Based Forward Modeling and Inversion Techniques for ...

Inhalt

This book investigates in detail the emerging deep learning (DL) technique in computational physics, assessing its promising potential to substitute conventional numerical solvers for calculating the fields in real-time. After good training, the proposed architecture can resolve both the forward computing and the inverse retrieve problems.

Bibliografische Angaben

Januar 2025, ca. 180 Seiten, Englisch
Taylor and Francis
978-1-032-50303-5

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