Bayesian Sequential Design
Bayesian Sequential Design is a statistical decision framework that iteratively updates beliefs about model parameters using Bayesian inference to guide the selection of subsequent experimental conditions in a sequential experimentation process.
154
Publications
7.5K
Citations
465
Authors
260
Institutions
Publications per year
2017–2026
46
Parents
154
1–5 of 154
465
5
h-index
4
h-index
4
h-index
The University of Texas MD Anderson Cancer Center, United States
4 publications · 441 citations
4
h-index
3
h-index
1–5 of 465
260
The University of Texas MD Anderson Cancer Center
Houston, United States
7 h-index
10 publications
1K citations

University of Waterloo
Waterloo, Canada
5 h-index
16 publications
265 citations
University of Maryland, College Park
College Park, United States
5 h-index
12 publications
396 citations
University of Oxford
Oxford, United Kingdom
5 h-index
6 publications
472 citations
Decision Sciences (United States)
Fort Walton Beach, United States
4 h-index
4 publications
171 citations
University of Michigan
Ann Arbor, United States
4 h-index
6 publications
202 citations
National Cancer Institute
Bethesda, United States
4 h-index
8 publications
525 citations
Ludwig-Maximilians-Universität München
Munich, Germany
4 h-index
4 publications
1.1K citations
1–8 of 260
14 publications · 854 citations
12
h-index
8 publications · 636 citations
8
h-index
7 publications · 544 citations
7
h-index
5 publications · 85 citations
5
h-index
4 publications · 127 citations
4
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1–5