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Model-agnostic variable importance for predictive uncertainty: an
  entropy-based approach

Model-agnostic variable importance for predictive uncertainty: an entropy-based approach

19 October 2023
Danny Wood
Theodore Papamarkou
Matt Benatan
Richard Allmendinger
    FAtt
    UD
ArXivPDFHTML

Papers citing "Model-agnostic variable importance for predictive uncertainty: an entropy-based approach"

2 / 2 papers shown
Title
Explaining Hyperparameter Optimization via Partial Dependence Plots
Explaining Hyperparameter Optimization via Partial Dependence Plots
Julia Moosbauer
J. Herbinger
Giuseppe Casalicchio
Marius Lindauer
Bernd Bischl
44
56
0
08 Nov 2021
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
261
9,134
0
06 Jun 2015
1