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Lowering the Entry Bar to HPC-Scale Uncertainty Quantification

Lowering the Entry Bar to HPC-Scale Uncertainty Quantification

27 April 2023
L. Seelinger
A. Reinarz
J. Bénézech
Mikkel B. Lykkegaard
L. Tamellini
Robert Scheichl
ArXiv (abs)PDFHTML

Papers citing "Lowering the Entry Bar to HPC-Scale Uncertainty Quantification"

7 / 7 papers shown
Title
Multilevel Delayed Acceptance MCMC
Multilevel Delayed Acceptance MCMC
Mikkel B. Lykkegaard
T. Dodwell
C. Fox
Grigorios Mingas
Robert Scheichl
49
15
0
08 Feb 2022
Multilevel Delayed Acceptance MCMC with an Adaptive Error Model in PyMC3
Multilevel Delayed Acceptance MCMC with an Adaptive Error Model in PyMC3
Mikkel B. Lykkegaard
Grigorios Mingas
Robert Scheichl
C. Fox
T. Dodwell
24
8
0
10 Dec 2020
The DUNE Framework: Basic Concepts and Recent Developments
The DUNE Framework: Basic Concepts and Recent Developments
P. Bastian
Markus Blatt
Andreas Dedner
Nils-Arne Dreier
C. Engwer
...
Christoph Grüninger
D. Kempf
Robert Klöfkorn
Mario Ohlberger
O. Sander
AI4CE
31
119
0
30 Sep 2019
Tune: A Research Platform for Distributed Model Selection and Training
Tune: A Research Platform for Distributed Model Selection and Training
Richard Liaw
Eric Liang
Robert Nishihara
Philipp Moritz
Joseph E. Gonzalez
Ion Stoica
209
903
0
13 Jul 2018
Dimension-independent likelihood-informed MCMC
Dimension-independent likelihood-informed MCMC
Tiangang Cui
K. Law
Youssef M. Marzouk
53
200
0
13 Nov 2014
Complexity Analysis of Accelerated MCMC Methods for Bayesian Inversion
Complexity Analysis of Accelerated MCMC Methods for Bayesian Inversion
V. H. Hoang
Christoph Schwab
Andrew M. Stuart
81
113
0
10 Jul 2012
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian
  Monte Carlo
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
Matthew D. Hoffman
Andrew Gelman
166
4,304
0
18 Nov 2011
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