Matthew L. Olson

Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences Between Pretrained Generative Models

Generative Adversarial Networks (GANs) are notoriously difficult to train especially for complex distributions and with limited data. This has driven the need for interpretable tools to audit trained networks, for example, to identify biases or ensure fairness. Existing GAN audit tools are restricte…