Spectral Normalization for Generative Adversarial Networks
One of the challenges in the study of generative adversarial networks is the instability of its training. In this paper, we propose a novel weight normalization technique called...
Publications
2 shownVirtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning
We propose a new regularization method based on virtual adversarial loss: a new measure of local smoothness of the conditional label distribution given input. Virtual adversaria...
Frequent Co-Authors
Researcher Info
- h-index
- 2
- Publications
- 2
- Citations
- 4,455
- Institution
- Kyoto College of Graduate Studies for Informatics
External Links
Identifiers
- ORCID
- 0000-0002-7363-1773
Impact Metrics
h-index
2
h-index: Number of publications with at least h citations each.