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Uncertainty Quantification of Surrogate Explanations: an Ordinal
  Consensus Approach

Uncertainty Quantification of Surrogate Explanations: an Ordinal Consensus Approach

17 November 2021
Jonas Schulz
Rafael Poyiadzi
Raúl Santos-Rodríguez
ArXivPDFHTML

Papers citing "Uncertainty Quantification of Surrogate Explanations: an Ordinal Consensus Approach"

3 / 3 papers shown
Title
Confident Feature Ranking
Confident Feature Ranking
Bitya Neuhof
Y. Benjamini
FAtt
32
3
0
28 Jul 2023
FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness,
  Accountability and Transparency Algorithms in Predictive Systems
FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems
Kacper Sokol
Alexander Hepburn
Rafael Poyiadzi
M. Clifford
Raúl Santos-Rodríguez
Peter A. Flach
35
29
0
08 Sep 2022
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,683
0
05 Dec 2016
1