Multi-Modal Causal Network Inference is a computational framework that integrates heterogeneous data modalities to reconstruct directed networks of causal relationships among biological variables, distinguishing itself by jointly modeling inter-modal dependencies and intra-modal dynamics within a unified probabilistic or machine learning architecture.
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Publications
146
Citations
17
Authors
3
Institutions
Publications per year
2017–2026
2
Parents
Publications
2
Towards Deconfounded Image-Text Matching with Causal Inference
Wenhui Li, Xinqi Su, Dan Song et al. · 2023 · 12 citations · Full text
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Authors
17
- PS
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- VP
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- JB
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- AJ
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- KL
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1–5 of 17
Institutions
3
University of Calgary
Calgary, Canada
1 h-index
3 publications
216 citations
University of Pittsburgh
Pittsburgh, United States
1 h-index
11 publications
814 citations
Carnegie Mellon University
Pittsburgh, United States
1 h-index
3 publications
222 citations
Tianjin University
Tianjin, China
1 publications
12 citations
Meizu (China)
Zhuhai, China
1 publications
12 citations
Donghua University
Shanghai, China
1 publications
14 citations
National University of Defense Technology
Changsha, China
1 publications
26 citations
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Venues
- Bioinformatics
1 publications · 74 citations
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- IEEE Access
1 publications · 72 citations
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- Advanced Engineering Informatics
1 publications · 14 citations
- Reliability Engineering & System Safety
1 publications · 26 citations
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