Fast Interpretable Greedy-Tree Sums is a research paper published in Proceedings of the National Academy of Sciences (2025). On theSindex it has a DataRank of 0.360. It has been cited 10 times.
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Linked data & code
DataRank reads this dataset's downstream impact straight off the citation graph β no black box, no proprietary weighting. How is this computed?
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Base Score Contribution
0.360
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology βHHS | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development
Grant: K23HD110716--01
National University of Singapore
Grant: A-8000448-00-00
NSF | CISE | Division of Information and Intelligent Systems
Grant: 1741340
BIGDATA: F: Scalable and Interpretable Machine Learning: Bridging Mechanistic and Data-Driven Modeling in the Biological Sciences
NSF | MPS | Division of Mathematical Sciences
Grant: 1613002 1953191 2015341 2209975 2031883 814639
NSF | CISE | Division of Computing and Communication Foundations
Grant: 0939370
Emerging Frontiers of Science of Information
DOD | USN | ONR | U.S. Naval Research Laboratory
Grant: N00014-17-1-2176
National Science Foundation
Grant: 1740855 2023505
NICHD NIH HHS
Grant: K23 HD110716
National Science Foundation
Grant: 2031883
Collaboration on the Theoretical Foundations of Deep Learning
National Science Foundation
Grant: 2015341
Understanding Complexity and the Bias-Variance Tradeoff in High Dimensions: Theory and Data Evidence
National Science Foundation
Grant: 1953191
Parallel Ensemble Learning and Feature Interaction Discovery: High Volume Dynamic Data
National Science Foundation
Grant: 2023505
Foundations of Data Science Institute
National Science Foundation
Grant: 1740855
TRIPODS: Berkeley Institute on the Foundations of Data Analysis
FWCI
11.03
Citation Percentile
1.0%
Citation Trend
Fields of Study
MeSH Terms
Keywords
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