The Bid Picture: Auction-Inspired Multi-player Generative Adversarial Networks Training

arXiv:2403.13866v1 Announce Type: new
Abstract: This article proposes auction-inspired multi-player generative adversarial networks training, which mitigates the mode collapse problem of GANs. Mode collapse occurs when an over-fitted generator generates a limited range of samples, often concentrating on a small subset of the data distribution. Despite the restricted diversity of generated samples, the discriminator can still be deceived into distinguishing these samples as real samples from the actual distribution. In the absence of external standards, a model cannot recognize its …

abstract adversarial article arxiv cs.ai cs.lg data distribution diversity gans generated generative generative adversarial networks generator networks samples small training type