982 citations · 2.8k across the 131 of their papers we have counts for
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stat.ML2017★ 113 cited
Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples
Kimin Lee, Honglak Lee, Kibok Lee +1
The problem of detecting whether a test sample is from in-distribution (i.e., training distribution by a classifier) or out-of-distribution sufficiently different from it arises in…
stat.ML2017
Gauging Variational Inference
Sungsoo Ahn, Michael Chertkov, Jinwoo Shin
Computing partition function is the most important statistical inference task arising in applications of Graphical Models (GM). Since it is computationally intractable, approximate…