BI-DCGAN: A Theoretically Grounded Bayesian Framework for Efficient and Diverse GANs

Mahsa Valizadeh, Rui Tuo, James Caverlee

Generative Adversarial Networks (GANs) are proficient at generating synthetic data but continue to suffer from mode collapse, where the generator produces a narrow range of outputs…