Adaptive Bayesian Inference
Adaptive Bayesian Inference is a probabilistic inference framework that dynamically updates belief distributions over latent variables or model parameters in response to sequential evidence, distinguishing itself from static Bayesian methods by incorporating feedback-driven adaptation of the inference process to optimize diagnostic accuracy in real-time.
253
Publications
14.3K
Citations
844
Authors
427
Institutions
Publications per year
2017–2026
78
Parents
253
Dose‐Finding Based on Efficacy–Toxicity Trade‐Offs
Peter F. Thall, John D. Cook · Biometrics · 2004 · 510 citations
1–5 of 253
844
The University of Texas MD Anderson Cancer Center, United States
6 publications · 819 citations
6
h-index
6
h-index
4
h-index
3
h-index
3
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1–5 of 844
427
The University of Texas MD Anderson Cancer Center
Houston, United States
11 h-index
35 publications
3.2K citations
The Ohio State University
Columbus, United States
8 h-index
20 publications
886 citations
University of Cambridge
Cambridge, United Kingdom
7 h-index
26 publications
984 citations
Berry & Associates (United States)
Dexter, United States
6 h-index
19 publications
651 citations
Tsinghua University
Beijing, China
5 h-index
14 publications
402 citations

Imperial College London
London, United Kingdom
5 h-index
16 publications
454 citations
University of California, Irvine
Irvine, United States
4 h-index
6 publications
156 citations
University of Oxford
Oxford, United Kingdom
4 h-index
8 publications
390 citations
1–8 of 427
Repository · 9 publications · 350 citations
9
h-index
7 publications · 943 citations
7
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7 publications · 407 citations
7
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6 publications · 475 citations
6
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5 publications · 715 citations
5
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1–5