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Most Relevant Explanation in Bayesian Networks

Most Relevant Explanation in Bayesian Networks

Journal of Artificial Intelligence Research (JAIR), 2011
16 January 2014
Changhe Yuan
Heejin Lim
Tsai-Ching Lu
    BDLFAtt
ArXiv (abs)PDFHTML

Papers citing "Most Relevant Explanation in Bayesian Networks"

6 / 6 papers shown
Motivating explanations in Bayesian networks using MAP-independence
Motivating explanations in Bayesian networks using MAP-independenceInternational Journal of Approximate Reasoning (IJAR), 2022
Johan Kwisthout
FAtt
149
4
0
05 Aug 2022
A Study of Automatic Metrics for the Evaluation of Natural Language
  Explanations
A Study of Automatic Metrics for the Evaluation of Natural Language ExplanationsConference of the European Chapter of the Association for Computational Linguistics (EACL), 2021
Miruna Clinciu
Arash Eshghi
H. Hastie
275
61
0
15 Mar 2021
A Taxonomy of Explainable Bayesian Networks
A Taxonomy of Explainable Bayesian Networks
I. Derks
A. D. Waal
BDLXAI
161
24
0
28 Jan 2021
Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time
  and Delay
Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time and Delay
Sasha Rubin
Thomas Gerspacher
Martin C. Cooper
Alexey Ignatiev
Nina Narodytska
FAtt
341
78
0
13 Aug 2020
Explainable Reinforcement Learning Through a Causal Lens
Explainable Reinforcement Learning Through a Causal LensAAAI Conference on Artificial Intelligence (AAAI), 2019
Prashan Madumal
Tim Miller
L. Sonenberg
F. Vetere
CML
348
403
0
27 May 2019
Evaluating computational models of explanation using human judgments
Evaluating computational models of explanation using human judgmentsConference on Uncertainty in Artificial Intelligence (UAI), 2013
M. Pacer
Joseph Jay Williams
Xinyu Chen
Tania Lombrozo
Thomas Griffiths
CMLFAtt
237
30
0
26 Sep 2013
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