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Identifying the Optimal Integration Time in Hamiltonian Monte Carlo

Identifying the Optimal Integration Time in Hamiltonian Monte Carlo

2 January 2016
M. Betancourt
ArXiv (abs)PDFHTML

Papers citing "Identifying the Optimal Integration Time in Hamiltonian Monte Carlo"

11 / 11 papers shown
Title
GIST: Gibbs self-tuning for locally adaptive Hamiltonian Monte Carlo
GIST: Gibbs self-tuning for locally adaptive Hamiltonian Monte Carlo
Nawaf Bou-Rabee
Bob Carpenter
Milo Marsden
156
7
0
23 Apr 2024
BlackJAX: Composable Bayesian inference in JAX
BlackJAX: Composable Bayesian inference in JAX
Alberto Cabezas
Adrien Corenflos
Junpeng Lao
Rémi Louf
Antoine Carnec
...
Kevin P. Murphy
Juan Camilo Orduz
Karm Patel
Xi Wang
Robert Zinkov
DRLMLAU
72
25
0
16 Feb 2024
Sequential Bayesian Learning for Hidden Semi-Markov Models
Sequential Bayesian Learning for Hidden Semi-Markov Models
Patrick Aschermayr
K. Kalogeropoulos
105
0
0
25 Jan 2023
Geometric Methods for Sampling, Optimisation, Inference and Adaptive
  Agents
Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agents
Alessandro Barp
Lancelot Da Costa
G. Francca
Karl J. Friston
Mark Girolami
Michael I. Jordan
G. Pavliotis
99
25
0
20 Mar 2022
Metropolis Adjusted Langevin Trajectories: a robust alternative to
  Hamiltonian Monte Carlo
Metropolis Adjusted Langevin Trajectories: a robust alternative to Hamiltonian Monte Carlo
L. Riou-Durand
Jure Vogrinc
90
15
0
26 Feb 2022
Efficient Learning of the Parameters of Non-Linear Models using
  Differentiable Resampling in Particle Filters
Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters
Conor Rosato
Vincent Beraud
P. Horridge
Thomas B. Schon
Simon Maskell
89
14
0
02 Nov 2021
Faster MCMC for Gaussian Latent Position Network Models
Faster MCMC for Gaussian Latent Position Network Models
Neil A. Spencer
B. Junker
T. Sweet
BDL
70
6
0
13 Jun 2020
Connecting the Dots: Numerical Randomized Hamiltonian Monte Carlo with
  State-Dependent Event Rates
Connecting the Dots: Numerical Randomized Hamiltonian Monte Carlo with State-Dependent Event Rates
T. S. Kleppe
58
12
0
04 May 2020
Adaptive Tuning Of Hamiltonian Monte Carlo Within Sequential Monte Carlo
Adaptive Tuning Of Hamiltonian Monte Carlo Within Sequential Monte Carlo
Alexander K. Buchholz
Nicolas Chopin
Pierre E. Jacob
90
34
0
23 Aug 2018
Modified Cholesky Riemann Manifold Hamiltonian Monte Carlo: Exploiting
  Sparsity for Fast Sampling of High-dimensional Targets
Modified Cholesky Riemann Manifold Hamiltonian Monte Carlo: Exploiting Sparsity for Fast Sampling of High-dimensional Targets
T. S. Kleppe
54
9
0
13 Dec 2016
On the Geometric Ergodicity of Hamiltonian Monte Carlo
On the Geometric Ergodicity of Hamiltonian Monte Carlo
Samuel Livingstone
M. Betancourt
Simon Byrne
Mark Girolami
141
117
0
29 Jan 2016
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