Unifying Information- and Optimization-theoretic approaches for modeling and training Generative Adversarial Networks

Engineering & Materials Science

1. Machine learning 100%
2. Deep neural networks 99%
3. Discriminators 84%
4. Sampling 71%
5. Electric power systems 57%
6. Learning algorithms 56%
7. Blueprints 45%
8. Information theory 39%
9. Inverse problems 36%
10. Seed 35%
11. Bayesian networks 34%
12. Network architecture 31%
13. Deep learning 30%
14. Tuning 26%
15. Students 25%
16. Decision making 24%
17. Planning 21%