Difference-Seeking Generative Adversarial Network--Unseen Sample Generation

no code implementations • ICLR 2020 • Yi Lin Sung, Sung-Hsien Hsieh, Soo-Chang Pei, Chun-Shien Lu

Unseen data, which are not samples from the distribution of training data and are difficult to collect, have exhibited importance in numerous applications, ({\em e. g.,} novelty detection, semi-supervised learning, and adversarial training).

Generative Adversarial Network Novelty Detection