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Massive parallelization boosts big Bayesian multidimensional scaling
v1v2 (latest)

Massive parallelization boosts big Bayesian multidimensional scaling

11 May 2019
Andrew J Holbrook
P. Lemey
G. Baele
S. Dellicour
D. Brockmann
A. Rambaut
M. Suchard
ArXiv (abs)PDFHTML

Papers citing "Massive parallelization boosts big Bayesian multidimensional scaling"

6 / 6 papers shown
Title
Sparse Bayesian multidimensional scaling(s)
Sparse Bayesian multidimensional scaling(s)
Ami D. Sheth
Aaron Smith
Andrew J. Holbrook
32
1
0
21 Jun 2024
Bayesian Hyperbolic Multidimensional Scaling
Bayesian Hyperbolic Multidimensional Scaling
Bolun Liu
Shane Lubold
A. Raftery
Tyler H. McCormick
54
4
0
26 Oct 2022
Parallel MCMC Algorithms: Theoretical Foundations, Algorithm Design,
  Case Studies
Parallel MCMC Algorithms: Theoretical Foundations, Algorithm Design, Case Studies
N. Glatt-Holtz
Andrew J Holbrook
J. Krometis
Cecilia F. Mondaini
71
12
0
10 Sep 2022
Generating MCMC proposals by randomly rotating the regular simplex
Generating MCMC proposals by randomly rotating the regular simplex
Andrew J Holbrook
55
8
0
13 Oct 2021
Vector operations for accelerating expensive Bayesian computations -- a
  tutorial guide
Vector operations for accelerating expensive Bayesian computations -- a tutorial guide
D. Warne
Scott A. Sisson
Christopher Drovandi Queensland University of Technology
62
4
0
25 Feb 2019
Prior-preconditioned conjugate gradient method for accelerated Gibbs
  sampling in "large $n$ & large $p$" Bayesian sparse regression
Prior-preconditioned conjugate gradient method for accelerated Gibbs sampling in "large nnn & large ppp" Bayesian sparse regression
A. Nishimura
M. Suchard
62
20
0
29 Oct 2018
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