543 citations · 821 across the 7 of their papers we have counts for
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cs.LG2019★ 2 cited
Improving performance of deep learning models with axiomatic attribution priors and expected gradients
Gabriel Erion, Joseph D. Janizek, Pascal Sturmfels +2
Recent research has demonstrated that feature attribution methods for deep networks can themselves be incorporated into training; these attribution priors optimize for a model whos…
cs.LG2019★ 267 cited
Explainable AI for Trees: From Local Explanations to Global Understanding
Scott M. Lundberg, Gabriel Erion, Hugh Chen +7
Tree-based machine learning models such as random forests, decision trees, and gradient boosted trees are the most popular non-linear predictive models used in practice today, yet…