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AI Explainability 360: Impact and Design

AI Explainability 360: Impact and Design

24 September 2021
Vijay Arya
Rachel K. E. Bellamy
Pin-Yu Chen
Amit Dhurandhar
Michael Hind
Samuel C. Hoffman
Stephanie Houde
Q. V. Liao
Ronny Luss
Aleksandra Mojsilović
Sami Mourad
Pablo Pedemonte
Ramya Raghavendra
John T. Richards
P. Sattigeri
Karthikeyan Shanmugam
Moninder Singh
Kush R. Varshney
Dennis L. Wei
Yunfeng Zhang
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Papers citing "AI Explainability 360: Impact and Design"

1 / 1 papers shown
Title
Towards A Rigorous Science of Interpretable Machine Learning
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
251
3,683
0
28 Feb 2017
1