Interpretable Modeling
Interpretable Modeling is a type of mathematical modeling that, as a genus, produces models whose structures and parameters are transparent and comprehensible to human analysts, and, as a differentia, explicitly prioritizes interpretability to enable understanding, validation, and trust in the model's reasoning and predictions.
1.5K
Publications
157.9K
Citations
6.1K
Authors
1.8K
Institutions
Publications per year
2017–2026
1.3K
Variants
Explainable Modeling
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Shanghai Jiao Tong University
Shanghai, China
21 h-index
110 publications
5.9K citations
Tsinghua University
Beijing, China
21 h-index
47 publications
3.1K citations
University of California, Berkeley
Berkeley, United States
19 h-index
45 publications
19K citations

Chinese Academy of Sciences
Beijing, China
19 h-index
76 publications
4.2K citations
Massachusetts Institute of Technology
Cambridge, United States
19 h-index
72 publications
9.4K citations
Harvard University
Cambridge, United States
18 h-index
56 publications
2.5K citations

Zhejiang University
Hangzhou, China
17 h-index
68 publications
3.4K citations
Stanford University
Stanford, United States
17 h-index
70 publications
5.5K citations
1–8 of 1.8K
Repository · 114 publications · 6K citations
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21 publications · 718 citations
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16 publications · 1.2K citations
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Repository · 21 publications · 480 citations
14
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15 publications · 657 citations
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