Machine Learning Attribution
Machine Learning Attribution is a scholarly contribution within computational linguistics and artificial intelligence that, as a formal framework or methodological construct, specifically enables the systematic identification and evaluation of source origins for proverbial expressions in digital text corpora through data-driven modeling and algorithmic inference.
51
Publications
6.2K
Citations
170
Authors
54
Institutions
Publications per year
2017–2026
41
Parents
51
Axiomatic Attribution for Deep Networks
Mukund Sundararajan, Ankur Taly, Qiqi Yan · arXiv (Cornell University) · 2017 · 2.6K citations · Full text
Axiomatic Attribution for Deep Networks
Mukund Sundararajan, Ankur Taly, Qiqi Yan · arXiv (Cornell University) · 2017 · 412 citations · Full text
Explaining a series of models by propagating Shapley values
Hugh Chen, Scott Lundberg, Su‐In Lee · Nature Communications · 2022 · 241 citations · Full text
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Google (United States)
Mountain View, United States
9 h-index
38 publications
10.4K citations
Stanford University
Stanford, United States
2 h-index
5 publications
442 citations
University of Antwerp
Antwerp, Belgium
2 h-index
5 publications
350 citations
University of Colorado Boulder
Boulder, United States
2 h-index
4 publications
141 citations

Harvard University Press
Cambridge, United States
2 h-index
3 publications
221 citations
University of California, Irvine
Irvine, United States
2 h-index
5 publications
159 citations
Microsoft Research (United Kingdom)
Cambridge, United Kingdom
1 h-index
1 publications
86 citations
Freie Universität Berlin
Berlin, Germany
1 h-index
2 publications
110 citations
1–8 of 54
Repository · 15 publications · 3.5K citations
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Conference · 2 publications · 93 citations
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Conference · 2 publications · 102 citations
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LLC · 2 publications · 214 citations
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2 publications · 56 citations
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