618 citations · 1.9k across the 59 of their papers we have counts for
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stat.ML2019★ 5 cited
Kernelized Complete Conditional Stein Discrepancy
Raghav Singhal, Xintian Han, Saad Lahlou +1
Much of machine learning relies on comparing distributions with discrepancy measures. Stein's method creates discrepancy measures between two distributions that require only the un…
stat.ML2019★ 42 cited
Support and Invertibility in Domain-Invariant Representations
Fredrik D. Johansson, David Sontag, Rajesh Ranganath
Learning domain-invariant representations has become a popular approach to unsupervised domain adaptation and is often justified by invoking a particular suite of theoretical resul…