85 citations · 206 across the 12 of their papers we have counts for
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stat.ML2023★ 14 cited
Explaining Predictive Uncertainty with Information Theoretic Shapley Values
David S. Watson, Joshua O'Hara, Niek Tax +2
Researchers in explainable artificial intelligence have developed numerous methods for helping users understand the predictions of complex supervised learning models. By contrast,…
stat.ML2023
Intervention Generalization: A View from Factor Graph Models
Gecia Bravo-Hermsdorff, David S. Watson, Jialin Yu +2
One of the goals of causal inference is to generalize from past experiments and observational data to novel conditions. While it is in principle possible to eventually learn a mapp…