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Interpretable Machine Learning for Discovery: Statistical Challenges \&
  Opportunities

Interpretable Machine Learning for Discovery: Statistical Challenges \& Opportunities

2 August 2023
Genevera I. Allen
Luqin Gan
Lili Zheng
ArXivPDFHTML

Papers citing "Interpretable Machine Learning for Discovery: Statistical Challenges \& Opportunities"

4 / 4 papers shown
Title
Visualization of Extremely Sparse Contingency Table by Taxicab
  Correspondence Analysis: A Case Study of Textual Data
Visualization of Extremely Sparse Contingency Table by Taxicab Correspondence Analysis: A Case Study of Textual Data
V. Choulakian
J. Allard
13
0
0
06 Aug 2023
Toward a Taxonomy of Trust for Probabilistic Machine Learning
Toward a Taxonomy of Trust for Probabilistic Machine Learning
Tamara Broderick
Andrew Gelman
Rachael Meager
Anna L. Smith
Tian Zheng
21
9
0
05 Dec 2021
Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and
  Goals of Human Trust in AI
Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AI
Alon Jacovi
Ana Marasović
Tim Miller
Yoav Goldberg
244
425
0
15 Oct 2020
Towards A Rigorous Science of Interpretable Machine Learning
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
225
3,672
0
28 Feb 2017
1