Deep Learning-Based Forward Modeling and Inversion Techniques for Computational Physics Problems, Hardback/Qiang Ren

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. Publisher: Taylor & Francis Ltd Author(s): Qiang Ren Illustration(s): 14 Tables, black and white; 83 Line drawings, black and white; 54 Halftones, black and white; 137 Illustrations, black and white Number of pages: 180 Publication date: 2023 Dimensions: 162 x 241 x 17 Cover type: Hardback