430 citations · 643 across the 26 of their papers we have counts for
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stat.ML2019★ 15 cited
A Random Matrix Perspective on Mixtures of Nonlinearities for Deep Learning
Ben Adlam, Jake Levinson, Jeffrey Pennington
One of the distinguishing characteristics of modern deep learning systems is that they typically employ neural network architectures that utilize enormous numbers of parameters, of…
stat.ML2019★ 10 cited
Investigating Under and Overfitting in Wasserstein Generative Adversarial Networks
Ben Adlam, Charles Weill, Amol Kapoor
We investigate under and overfitting in Generative Adversarial Networks (GANs), using discriminators unseen by the generator to measure generalization. We find that the model capac…