438 citations · 979 across the 11 of their papers we have counts for
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stat.ML2014★ 43 cited
Learning Ordered Representations with Nested Dropout
Oren Rippel, Michael A. Gelbart, Ryan P. Adams
In this paper, we study ordered representations of data in which different dimensions have different degrees of importance. To learn these representations we introduce nested dropo…
stat.ML2014★ 79 cited
Avoiding pathologies in very deep networks
David Duvenaud, Oren Rippel, Ryan P. Adams +1
Choosing appropriate architectures and regularization strategies for deep networks is crucial to good predictive performance. To shed light on this problem, we analyze the analogou…