101 citations · 214 across the 17 of their papers we have counts for
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stat.ME2019★ 2 cited
A Bayesian nonparametric test for conditional independence
Onur Teymur, Sarah Filippi
This article introduces a Bayesian nonparametric method for quantifying the relative evidence in a dataset in favour of the dependence or independence of two variables conditional…
stat.ML2019★ 9 cited
Interpreting Deep Neural Networks Through Variable Importance
Jonathan Ish-Horowicz, Dana Udwin, Seth Flaxman +2
While the success of deep neural networks (DNNs) is well-established across a variety of domains, our ability to explain and interpret these methods is limited. Unlike previously p…