Physics-Informed Conditional Generative Adversarial Network for Inverse Electromagnetic Problems-Reference-Cited by-同舟云学术

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Physics-Informed Conditional Generative Adversarial Network for Inverse Electromagnetic Problems

Published:2024-06-02 Issue: Volume:abs/1411.1784 Page:1-2
ISSN:
Container-title:2024 IEEE 21st Biennial Conference on Electromagnetic Field Computation (CEFC)
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Author:

Akbari Amir¹,Lowther David¹

Affiliation:

1. McGill University,Department of Electrical and Computer Engineering,Montreal,Canada

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10585268/10585609/10585612.pdf?arnumber=10585612

Reference11 articles.

1. Evolutionary Multiobjective Optimization Methods for the Shape Design of Industrial Electromagnetic Devices

2. Deep Learning for Magnetic Field Estimation

3. Physics-Informed Neural Networks for Inverse Electromagnetic Problems

4. A Numerical Twin Model for the Coupled Field Analysis of TEAM Workshop Problem 36

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