1.5k citations · 1.9k across the 8 of their papers we have counts for
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stat.ML2018
Metropolis-Hastings Generative Adversarial Networks
Ryan Turner, Jane Hung, Eric Frank +2
We introduce the Metropolis-Hastings generative adversarial network (MH-GAN), which combines aspects of Markov chain Monte Carlo and GANs. The MH-GAN draws samples from the distrib…
stat.ML2017★ 2 cited
Proceedings of NIPS 2017 Symposium on Interpretable Machine Learning
Andrew Gordon Wilson, Jason Yosinski, Patrice Simard +2
This is the Proceedings of NIPS 2017 Symposium on Interpretable Machine Learning, held in Long Beach, California, USA on December 7, 2017
stat.ML2017★ 226 cited
SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability
Maithra Raghu, Justin Gilmer, Jason Yosinski +1
We propose a new technique, Singular Vector Canonical Correlation Analysis (SVCCA), a tool for quickly comparing two representations in a way that is both invariant to affine trans…