2.6k citations · 5.6k across the 24 of their papers we have counts for
5 papers · 1 filter
Discriminator Rejection Sampling
Samaneh Azadi, Catherine Olsson, Trevor Darrell +2
We propose a rejection sampling scheme using the discriminator of a GAN to approximately correct errors in the GAN generator distribution. We show that under quite strict assumptio…
Skill Rating for Generative Models
Catherine Olsson, Surya Bhupatiraju, Tom Brown +2
We explore a new way to evaluate generative models using insights from evaluation of competitive games between human players. We show experimentally that tournaments between genera…
TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing
Augustus Odena, Ian Goodfellow
Machine learning models are notoriously difficult to interpret and debug. This is particularly true of neural networks. In this work, we introduce automated software testing techni…
Self-Attention Generative Adversarial Networks
Han Zhang, Ian Goodfellow, Dimitris Metaxas +1
In this paper, we propose the Self-Attention Generative Adversarial Network (SAGAN) which allows attention-driven, long-range dependency modeling for image generation tasks. Tradit…
Is Generator Conditioning Causally Related to GAN Performance?
Augustus Odena, Jacob Buckman, Catherine Olsson +4
Recent work (Pennington et al, 2017) suggests that controlling the entire distribution of Jacobian singular values is an important design consideration in deep learning. Motivated…