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Bayesian sparse reconstruction: a brute-force approach to astronomical
  imaging and machine learning
v1v2 (latest)

Bayesian sparse reconstruction: a brute-force approach to astronomical imaging and machine learning

12 September 2018
E. Higson
Will Handley
Michael P. Hobson
A. Lasenby
ArXiv (abs)PDFHTML

Papers citing "Bayesian sparse reconstruction: a brute-force approach to astronomical imaging and machine learning"

4 / 4 papers shown
Title
Nested sampling for physical scientists
Nested sampling for physical scientists
G. Ashton
N. Bernstein
Johannes Buchner
Xi Chen
Gábor Csányi
...
Leah F. South
J. Veitch
Philipp Wacker
D. Wales
David Yallup
114
82
0
31 May 2022
Compromise-free Bayesian neural networks
Compromise-free Bayesian neural networks
K. Javid
Will Handley
Michael P. Hobson
A. Lasenby
UQCVBDL
68
8
0
25 Apr 2020
dynesty: A Dynamic Nested Sampling Package for Estimating Bayesian
  Posteriors and Evidences
dynesty: A Dynamic Nested Sampling Package for Estimating Bayesian Posteriors and Evidences
J. Speagle
93
1,223
0
03 Apr 2019
Dynamic nested sampling: an improved algorithm for parameter estimation
  and evidence calculation
Dynamic nested sampling: an improved algorithm for parameter estimation and evidence calculation
E. Higson
Will Handley
Michael P. Hobson
A. Lasenby
97
197
0
11 Apr 2017
1