Location Priors
Location Priors is a type of prior distribution in Bayesian inference that incorporates domain-specific knowledge about the probable values of a model’s location parameters, distinguishing itself by encoding expectations about the central tendency or spatial positioning of parameters within a parameter space.
55
Publications
6.6K
Citations
154
Authors
82
Institutions
Publications per year
2017–2026
5
55
Monocular 3D Object Detection for Autonomous Driving
Xiaozhi Chen, Kaustav Kundu, Ziyu Zhang et al. · 2016 · 1.1K citations
Bogdan Alexe, Thomas Deselaers, Vittorio Ferrari · 2010 · 804 citations
On the Consistency of Bayes Estimates
Persi Diaconis, David A. Freedman · The Annals of Statistics · 1986 · 624 citations
Depth saliency based on anisotropic center-surround difference
Ran Ju, Ling Ge, Wenjing Geng et al. · 2014 · 518 citations
1–5 of 55
154
3
h-index
3
h-index
2
h-index
2
h-index
2
h-index
1–5 of 154
82

University of Warwick
Coventry, United Kingdom
5 h-index
9 publications
989 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
5 publications
120 citations
The University of Tokyo
Tokyo, Japan
3 h-index
3 publications
55 citations
Wellcome Centre for Human Neuroimaging
London, United Kingdom
2 h-index
7 publications
238 citations
National University of Singapore
Singapore, Singapore
2 h-index
4 publications
93 citations
Simón Bolívar University
Caracas, Venezuela
2 h-index
4 publications
58 citations

University of Cagliari
Cagliari, Italy
2 h-index
4 publications
86 citations

Centre National de la Recherche Scientifique
Paris, France
2 h-index
6 publications
115 citations
1–8 of 82
6 publications · 548 citations
6
h-index
5 publications · 827 citations
5
h-index
TPAMI · 3 publications · 1.3K citations
3
h-index
2 publications · 70 citations
2
h-index
2 publications · 64 citations
2
h-index
1–5