1.7k citations · 3.2k across the 31 of their papers we have counts for
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stat.ML2020★ 55 cited
Uses and Abuses of the Cross-Entropy Loss: Case Studies in Modern Deep Learning
Elliott Gordon-Rodriguez, Gabriel Loaiza-Ganem, Geoff Pleiss +1
Modern deep learning is primarily an experimental science, in which empirical advances occasionally come at the expense of probabilistic rigor. Here we focus on one such example; n…
stat.ML2020★ 3 cited
Deep Sigma Point Processes
Martin Jankowiak, Geoff Pleiss, Jacob R. Gardner
We introduce Deep Sigma Point Processes, a class of parametric models inspired by the compositional structure of Deep Gaussian Processes (DGPs). Deep Sigma Point Processes (DSPPs)…