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Sampling using Adaptive Regenerative Processes

Sampling using Adaptive Regenerative Processes

18 October 2022
Hector McKimm
Andi Q. Wang
M. Pollock
Christian P. Robert
Gareth O. Roberts
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Papers citing "Sampling using Adaptive Regenerative Processes"

4 / 4 papers shown
Title
Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov
  Chain Monte Carlo Methods
Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov Chain Monte Carlo Methods
Marylou Gabrié
Grant M. Rotskoff
Eric Vanden-Eijnden
34
20
0
16 Jul 2021
Normalizing Flows for Probabilistic Modeling and Inference
Normalizing Flows for Probabilistic Modeling and Inference
George Papamakarios
Eric T. Nalisnick
Danilo Jimenez Rezende
S. Mohamed
Balaji Lakshminarayanan
TPM
AI4CE
139
1,662
0
05 Dec 2019
The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis
  of Big Data
The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data
J. Bierkens
Paul Fearnhead
Gareth O. Roberts
67
232
0
11 Jul 2016
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
142
4,275
0
18 Nov 2011
1