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Rapid Mixing of Hamiltonian Monte Carlo on Strongly Log-Concave
  Distributions

Rapid Mixing of Hamiltonian Monte Carlo on Strongly Log-Concave Distributions

23 August 2017
Oren Mangoubi
Aaron Smith
ArXivPDFHTML

Papers citing "Rapid Mixing of Hamiltonian Monte Carlo on Strongly Log-Concave Distributions"

16 / 16 papers shown
Title
Hamiltonian Adaptive Importance Sampling
Hamiltonian Adaptive Importance Sampling
Ali Mousavi
R. Monsefi
Victor Elvira
28
13
0
27 Sep 2022
Order-based Structure Learning without Score Equivalence
Order-based Structure Learning without Score Equivalence
Hyunwoong Chang
James Cai
Quan Zhou
CML
OffRL
19
3
0
10 Feb 2022
Hamiltonian Monte Carlo with Asymmetrical Momentum Distributions
Hamiltonian Monte Carlo with Asymmetrical Momentum Distributions
Soumyadip Ghosh
Ying-Ling Lu
Aditya Gopalan
14
3
0
21 Oct 2021
When is the Convergence Time of Langevin Algorithms Dimension
  Independent? A Composite Optimization Viewpoint
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint
Y. Freund
Yi-An Ma
Tong Zhang
29
16
0
05 Oct 2021
Asymptotic bias of inexact Markov Chain Monte Carlo methods in high
  dimension
Asymptotic bias of inexact Markov Chain Monte Carlo methods in high dimension
Alain Durmus
A. Eberle
24
19
0
02 Aug 2021
Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems
Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems
Aman Sinha
Matthew O'Kelly
Russ Tedrake
John C. Duchi
39
47
0
24 Aug 2020
Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of
  Multimodal Posteriors
Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors
Yuling Yao
Aki Vehtari
Andrew Gelman
29
60
0
22 Jun 2020
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized
  Hamiltonian Monte Carlo
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo
Y. Lee
Ruoqi Shen
Kevin Tian
17
37
0
10 Feb 2020
Estimating Convergence of Markov chains with L-Lag Couplings
Estimating Convergence of Markov chains with L-Lag Couplings
N. Biswas
Pierre E. Jacob
Paul Vanetti
17
47
0
23 May 2019
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural
  Transport
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport
Matthew Hoffman
Pavel Sountsov
Joshua V. Dillon
I. Langmore
Dustin Tran
Srinivas Vasudevan
BDL
24
103
0
09 Mar 2019
Sampling as optimization in the space of measures: The Langevin dynamics
  as a composite optimization problem
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem
Andre Wibisono
13
177
0
22 Feb 2018
Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal
  Distributions using Simulated Tempering Langevin Monte Carlo
Beyond Log-concavity: Provable Guarantees for Sampling Multi-modal Distributions using Simulated Tempering Langevin Monte Carlo
Rong Ge
Holden Lee
Andrej Risteski
13
53
0
07 Oct 2017
Unbiased Hamiltonian Monte Carlo with couplings
Unbiased Hamiltonian Monte Carlo with couplings
J. Heng
Pierre E. Jacob
18
63
0
01 Sep 2017
Underdamped Langevin MCMC: A non-asymptotic analysis
Underdamped Langevin MCMC: A non-asymptotic analysis
Xiang Cheng
Niladri S. Chatterji
Peter L. Bartlett
Michael I. Jordan
36
293
0
12 Jul 2017
Rapid Mixing of Geodesic Walks on Manifolds with Positive Curvature
Rapid Mixing of Geodesic Walks on Manifolds with Positive Curvature
Oren Mangoubi
Aaron Smith
OT
16
22
0
09 Sep 2016
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
185
3,262
0
09 Jun 2012
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