ProbGAN: Towards Probabilistic GAN with Theoretical Guarantees

By Hao He, Hao Wang, Guang-He Lee, Yonglong Tian. 2018

32 citations recorded by the source corpus.

Subfields: Generative Models, Probabilistic & Bayesian Methods

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Generative Models

1. Dit-Yan Yeung
2. Hao Wang
3. Xingjian Shi

In Probabilistic & Bayesian Methods

1. Dit-Yan Yeung
2. Hao Wang

Citations in the corpus

• AutoGAN: Neural Architecture Search for Generative Adversarial Networks (2019, neutral): “13 ProbGAN[14] 7.”
• A Survey on Bayesian Deep Learning (2016, background): “Later on, Bayesian formulations (as well as related theoretical results) for GAN have also been proposed [30, 37].”
• AdversarialNAS: Adversarial Neural Architecture Search for GANs (2019, unknown): “13 − ProbGAN [16] 7.”