Bayesian Inference
Bayesian Inference is a statistical inference method that updates the probability for a hypothesis as evidence accumulates, by applying Bayes' theorem with a prior distribution to obtain a posterior distribution that reflects refined beliefs about model parameters.
36.4K
Publications
3M
Citations
56.2K
Authors
8.3K
Institutions
Publications per year
2017–2026
8.6K
36.4K
Nearest neighbor pattern classification
Thomas M. Cover, Peter E. Hart · IEEE Transactions on Information Theory · 1967 · 16.1K citations
Auto-Encoding Variational Bayes
Diederik P. Kingma, Max Welling · UvA-DARE (University of Amsterdam) · 2013 · 15.6K citations · Full text
1–5 of 36.4K
56.2K
57
h-index
55
h-index
55
h-index
50
h-index
49
h-index
1–5 of 56.2K
8.3K
University College London
London, United Kingdom
125 h-index
966 publications
138.6K citations
Stanford University
Stanford, United States
122 h-index
727 publications
128.4K citations
University of California, Berkeley
Berkeley, United States
109 h-index
709 publications
90.9K citations
Duke University
Durham, United States
105 h-index
905 publications
77.7K citations
Carnegie Mellon University
Pittsburgh, United States
97 h-index
756 publications
93.6K citations
University of Chicago
Chicago, United States
97 h-index
414 publications
78.4K citations
University of Washington
Seattle, United States
95 h-index
616 publications
99.6K citations
University of Cambridge
Cambridge, United Kingdom
95 h-index
928 publications
72.3K citations
1–8 of 8.3K
1.1K publications · 219.7K citations
201
h-index
347 publications · 87.6K citations
126
h-index
Repository · 1.5K publications · 85.5K citations
117
h-index
530 publications · 73.4K citations
117
h-index
502 publications · 73.5K citations
112
h-index
1–5