Causal Feature Selection
Causal Feature Selection is a computational methodology within multi-omics causal inference that identifies subsets of variables exhibiting causal relationships with an outcome of interest, distinguishing itself from associative or predictive feature selection by explicitly inferring directionality and causal mechanisms from observational or experimental multi-omics data.
52
Publications
2.8K
Citations
161
Authors
80
Institutions
Publications per year
2017–2026
35
Parents
52
Extended BIC for small-n-large-P sparse GLM
Jiahua Chen, Zehua Chen · Statistica Sinica · 2011 · 201 citations
Computing, Biostatistics, Genetics +16
Multi-Source Causal Feature Selection
Kui Yu, Lin Liu, Jiuyong Li et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence · 2019 · 117 citations
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80

Hefei University of Technology
Hefei, China
13 h-index
27 publications
1K citations

University of South Australia
Adelaide, Australia
8 h-index
18 publications
1.1K citations
University of Science and Technology of China
Hefei, China
5 h-index
12 publications
793 citations
Hangzhou Normal University
Hangzhou, China
3 h-index
3 publications
143 citations
Nanyang Technological University
Singapore, Singapore
3 h-index
4 publications
232 citations
New York University
New York, United States
3 h-index
5 publications
1.3K citations

Chinese Academy of Sciences
Beijing, China
3 h-index
6 publications
396 citations
University of Pittsburgh
Pittsburgh, United States
2 h-index
8 publications
188 citations
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Repository · 4 publications · 89 citations
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3 publications · 99 citations
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2 publications · 65 citations
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Conference · 2 publications · 68 citations
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JMLR · 2 publications · 217 citations
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