Bayesian Predictive Synthesis
Bayesian Predictive Synthesis is a Bayesian framework for combining predictive distributions from multiple models or experts by explicitly modeling their dependencies and assigning dynamic, context-dependent weights through a hierarchical prior structure.
16
Publications
3K
Citations
41
Authors
27
Institutions
Publications per year
2017–2026
6
Parents
16
Bayesian reaction optimization as a tool for chemical synthesis
Benjamin J. Shields, Jason M. Stevens, Jun Li et al. · Nature · 2021 · 1K citations
1–5 of 16
41
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1–5 of 41
27
Duke University
Durham, United States
4 h-index
8 publications
1.8K citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
2 publications
1.1K citations

University of Minnesota
Minneapolis, United States
2 h-index
2 publications
1.1K citations
Michigan State University
East Lansing, United States
1 h-index
2 publications
34 citations

Imperial College London
London, United Kingdom
1 h-index
1 publications
14 citations
Vienna University of Economics and Business
Vienna, Austria
1 h-index
1 publications
13 citations

Aarhus University
Aarhus, Denmark
1 h-index
1 publications
51 citations

Agricultural Research Service
Washington, United States
1 h-index
1 publications
17 citations
1–8 of 27
3 publications · 1.2K citations
3
h-index
2 publications · 543 citations
2
h-index
2 publications · 38 citations
2
h-index
1 publications · 116 citations
1
h-index
1 publications · 36 citations
1
h-index
1–5