Bayesian Population Synthesis
Bayesian Population Synthesis is a statistical framework for generating synthetic populations by estimating individual-level attributes through Bayesian inference, distinguishing itself from alternative methods by incorporating prior knowledge and uncertainty quantification into the probabilistic reconstruction of population structures from marginal and joint distributions.
29
Publications
1.3K
Citations
119
Authors
58
Institutions
Publications per year
2017–2026
10
29
1–5 of 29
119
9
h-index
6
h-index
4
h-index
4
h-index
3
h-index
1–5 of 119
58
MRC Biostatistics Unit
Cambridge, United Kingdom
8 h-index
18 publications
908 citations
Medical Research Council
London, United Kingdom
5 h-index
19 publications
1.1K citations

University of Bristol
Bristol, United Kingdom
4 h-index
5 publications
317 citations

Imperial College London
London, United Kingdom
3 h-index
6 publications
263 citations
Health Protection Agency
Malé, Maldives
3 h-index
3 publications
200 citations
University College London
London, United Kingdom
3 h-index
3 publications
142 citations
London School of Hygiene & Tropical Medicine
London, United Kingdom
3 h-index
3 publications
203 citations

Vrije Universiteit Amsterdam
Amsterdam, The Netherlands
2 h-index
4 publications
160 citations
1–8 of 58
2 publications · 112 citations
2
h-index
RSRS · 1 publications · 18 citations
1
h-index
1 publications · 30 citations
1
h-index
PRD · 1 publications · 92 citations
1
h-index
1 publications · 36 citations
1
h-index
1–5