Discovering Pareto-Optimal Magnetic-Design Solutions via a Generative Adversarial Network
Author:
Affiliation:
1. Department of Optimization, Fraunhofer Institute for Industrial Mathematics ITWM, Kaiserslautern, Germany
2. Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Electronic, Optical and Magnetic Materials
Link
http://xplorestaging.ieee.org/ielx7/20/9868170/09770829.pdf?arnumber=9770829
Reference16 articles.
1. Accelerating CS-MRI Reconstruction With Fine-Tuning Wasserstein Generative Adversarial Network
2. On Antenna Q-factor Characterization with Generative Adversarial Networks
3. Learning-Based Fast Electromagnetic Scattering Solver Through Generative Adversarial Network
4. Evolutionary Multiobjective Optimization Driven by Generative Adversarial Networks (GANs)
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