Dynamic Hypothesis Generation
Dynamic Hypothesis Generation is a systematic methodological approach within causal inference that enables the iterative formulation and refinement of causal hypotheses through feedback-rich modeling environments, distinguishing itself from static hypothesis formulation by explicitly incorporating temporal and systemic interactions in complex adaptive systems.
16
Publications
497
Citations
43
Authors
24
Institutions
Publications per year
2017–2026
3
Parents
16
Dynamic and hierarchical multi-structure geometric model fitting
Hoi Sim Wong, Tat-Jun Chin, Jin Yu et al. · 2011 · 141 citations
Extreme learning machine towards dynamic model hypothesis in fish ethology research
Rui Nian, Bo He, Bing Zheng et al. · Neurocomputing · 2013 · 55 citations
SpatialAgent: An autonomous AI agent for spatial biology
Hanchen Wang, Yichun He, Paula P. Coelho et al. · bioRxiv (Cold Spring Harbor Laboratory) · 2025 · 42 citations · Full text
Computing, Biology, Computer Science +12
Yorick Wilks, David Farwell, Afzal Ballim et al. · 1989 · 33 citations · Full text
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24
George Mason University
Fairfax, United States
2 h-index
4 publications
114 citations

Birkbeck, University of London
London, United Kingdom
2 h-index
4 publications
60 citations
University of Oklahoma
Norman, United States
2 h-index
4 publications
60 citations
University at Buffalo, State University of New York
Buffalo, United States
2 h-index
5 publications
95 citations
Northwestern University
Laoag, Philippines
1 h-index
1 publications
23 citations
Rutgers Sexual and Reproductive Health and Rights
Utrecht, Netherlands
1 h-index
1 publications
10 citations

The University of Adelaide
Adelaide, Australia
1 h-index
4 publications
564 citations
Systems Biology Institute
Tokyo, Japan
1 h-index
1 publications
24 citations
1–8 of 24
1 publications · 10 citations
1
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1 publications · 55 citations
1
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1 publications · 23 citations
1
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1 publications · 17 citations
1
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Conference · 1 publications · 14 citations
1
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1–5