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1
A Quantitative Comparison of Causality and Feature Relevanc..:
, In:
Artificial Intelligence in HCI; Lecture Notes in Computer Science
,
Rawal, Atul
;
McCoy, James
;
Raglin, Adrienne
. - p. 274-285 , 2023
Link:
https://doi.org/10.1007/978-3-031-35891-3_17
RT T1 <cTitle>Artificial Intelligence in HCI; Lecture Notes in Computer Science</cTitle>: T1 <Title>A Quantitative Comparison of Causality and Feature Relevance via Explainable AI (XAI) for Robust, and Trustworthy Artificial Reasoning Systems</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1007_978-3-031-35891-3_17&Exemplar=1&LAN=DE A1 Rawal, Atul A1 McCoy, James A1 Raglin, Adrienne A1 Rawat, Danda B. PB Springer Nature Switzerland YR 2023 SP 274 OP 285 LK http://dx.doi.org/https://doi.org/10.1007/978-3-031-35891-3_17 DO https://doi.org/10.1007/978-3-031-35891-3_17 SF ELIB - SuUB Bremen
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