1.4k citations · 8.8k across the 91 of their papers we have counts for
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stat.CO2014★ 38 cited
Hamiltonian Monte Carlo Without Detailed Balance
Jascha Sohl-Dickstein, Mayur Mudigonda, Michael R. DeWeese
We present a method for performing Hamiltonian Monte Carlo that largely eliminates sample rejection for typical hyperparameters. In situations that would normally lead to rejection…
cs.NE2014★ 69 cited
Analyzing noise in autoencoders and deep networks
Ben Poole, Jascha Sohl-Dickstein, Surya Ganguli
Autoencoders have emerged as a useful framework for unsupervised learning of internal representations, and a wide variety of apparently conceptually disparate regularization techni…