385 citations · 1.1k across the 18 of their papers we have counts for
4 papers · 1 filter
Understanding the Role of Individual Units in a Deep Neural Network
David Bau, Jun-Yan Zhu, Hendrik Strobelt +3
Deep neural networks excel at finding hierarchical representations that solve complex tasks over large data sets. How can we humans understand these learned representations? In thi…
Semantic Photo Manipulation with a Generative Image Prior
David Bau, Hendrik Strobelt, William Peebles +4
Despite the recent success of GANs in synthesizing images conditioned on inputs such as a user sketch, text, or semantic labels, manipulating the high-level attributes of an existi…
Seeing What a GAN Cannot Generate
David Bau, Jun-Yan Zhu, Jonas Wulff +4
Despite the success of Generative Adversarial Networks (GANs), mode collapse remains a serious issue during GAN training. To date, little work has focused on understanding and quan…
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
David Bau, Jun-Yan Zhu, Hendrik Strobelt +4
Generative Adversarial Networks (GANs) have recently achieved impressive results for many real-world applications, and many GAN variants have emerged with improvements in sample qu…