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2306.05724
Cited By
Explaining Predictive Uncertainty with Information Theoretic Shapley Values
9 June 2023
David S. Watson
Joshua O'Hara
Niek Tax
Richard Mudd
Ido Guy
TDI
FAtt
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Papers citing
"Explaining Predictive Uncertainty with Information Theoretic Shapley Values"
13 / 13 papers shown
Title
A Comprehensive Study of Shapley Value in Data Analytics
Hong Lin
Shixin Wan
Zhongle Xie
Ke Chen
Meihui Zhang
Lidan Shou
Gang Chen
90
0
0
02 Dec 2024
Segmentation, Classification and Interpretation of Breast Cancer Medical Images using Human-in-the-Loop Machine Learning
David Vázquez-Lema
E. Mosqueira-Rey
Elena Hernández-Pereira
Carlos Fernández-Lozano
Fernando Seara-Romera
Jorge Pombo-Otero
LM&MA
19
1
0
29 Mar 2024
Uncertainty in Graph Neural Networks: A Survey
Fangxin Wang
Yuqing Liu
Kay Liu
Yibo Wang
Sourav Medya
Philip S. Yu
AI4CE
46
8
0
11 Mar 2024
Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration
Julian Rodemann
Federico Croppi
Philipp Arens
Yusuf Sale
J. Herbinger
B. Bischl
Eyke Hüllermeier
Thomas Augustin
Conor J. Walsh
Giuseppe Casalicchio
44
7
0
07 Mar 2024
Uncertainty quantification for probabilistic machine learning in earth observation using conformal prediction
Geethen Singh
Glenn Moncrieff
Zander Venter
Kerry Cawse-Nicholson
Jasper Slingsby
Tamara B. Robinson
21
13
0
12 Jan 2024
Identifying Drivers of Predictive Aleatoric Uncertainty
Pascal Iversen
Simon Witzke
Katharina Baum
Bernhard Y. Renard
UD
43
1
0
12 Dec 2023
A Comparative Study of Methods for Estimating Conditional Shapley Values and When to Use Them
Lars Henry Berge Olsen
I. Glad
Martin Jullum
K. Aas
FAtt
46
12
0
16 May 2023
Efficient SAGE Estimation via Causal Structure Learning
C. Luther
Gunnar Konig
Moritz Grosse-Wentrup
29
3
0
06 Apr 2023
From Shapley Values to Generalized Additive Models and back
Sebastian Bordt
U. V. Luxburg
FAtt
TDI
53
34
0
08 Sep 2022
Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates
Dan Ley
Umang Bhatt
Adrian Weller
UQCV
168
21
0
05 Dec 2021
Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations
N. Jethani
Mukund Sudarshan
Yindalon Aphinyanagphongs
Rajesh Ranganath
FAtt
78
70
0
02 Mar 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,652
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,109
0
06 Jun 2015
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