Approximate Bayesian Model Averaging
Approximate Bayesian Model Averaging is a computational method in Bayesian statistics that approximates the full Bayesian model averaging process by simplifying the model space exploration or posterior probability calculations to make inference more tractable under limited computational resources.
17
Publications
1.1K
Citations
52
Authors
41
Institutions
Publications per year
2017–2026
7
Parents
17
Approximate Bayesian neural networks in genomic prediction
Patrik Waldmann · Genetics Selection Evolution · 2018 · 55 citations · Full text
Marjan Moazamnia, Yousef Hassanzadeh, Ata Allah Nadiri et al. · Journal of Hydrology · 2019 · 48 citations
1–5 of 17
52
1
h-index
Universidade Federal do Rio Grande do Sul, Brazil
1 publications · 25 citations
1
h-index
Centre de Biologie pour la Gestion des Populations, France
1 publications · 14 citations
1
h-index
1 publications · 44 citations
1
h-index
1
h-index
1–5 of 52
41
University of Wisconsin–Madison
Madison, United States
2 h-index
5 publications
92 citations

Agropolis International
Montpellier, France
1 h-index
2 publications
28 citations

University of Wisconsin System
Madison, United States
1 h-index
2 publications
24 citations
Institut National de la Statistique et des Etudes Economiques
Paris, France
1 h-index
1 publications
38 citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
1 h-index
2 publications
56 citations

Harvard University Press
Cambridge, United States
1 h-index
1 publications
19 citations
Centre de Biologie pour la Gestion des Populations
Montferrier-sur-Lez, France
1 h-index
2 publications
28 citations
Seoul National University
Seoul, South Korea
1 h-index
1 publications
15 citations
1–8 of 41
2 publications · 525 citations
2
h-index
1 publications · 48 citations
1
h-index
JDS · 1 publications · 12 citations
1
h-index
MBR · 1 publications · 28 citations
1
h-index
1 publications · 44 citations
1
h-index
1–5