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Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space

Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space

3 February 2022
Yunbum Kook
Y. Lee
Ruoqi Shen
Santosh Vempala
ArXivPDFHTML

Papers citing "Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space"

14 / 14 papers shown
Title
New affine invariant ensemble samplers and their dimensional scaling
New affine invariant ensemble samplers and their dimensional scaling
Yifan Chen
81
0
0
05 May 2025
Condition-number-independent convergence rate of Riemannian Hamiltonian
  Monte Carlo with numerical integrators
Condition-number-independent convergence rate of Riemannian Hamiltonian Monte Carlo with numerical integrators
Yunbum Kook
Y. Lee
Ruoqi Shen
Santosh Vempala
73
12
0
13 Oct 2022
Volesti: Volume Approximation and Sampling for Convex Polytopes in R
Volesti: Volume Approximation and Sampling for Convex Polytopes in R
Apostolos Chalkis
Vissarion Fisikopoulos
25
25
0
03 Jul 2020
Exponential ergodicity of mirror-Langevin diffusions
Exponential ergodicity of mirror-Langevin diffusions
Sinho Chewi
Thibaut Le Gouic
Chen Lu
Tyler Maunu
Philippe Rigollet
Austin J. Stromme
52
51
0
19 May 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
47
37
0
10 Feb 2020
Introducing an Explicit Symplectic Integration Scheme for Riemannian
  Manifold Hamiltonian Monte Carlo
Introducing an Explicit Symplectic Integration Scheme for Riemannian Manifold Hamiltonian Monte Carlo
Adam D. Cobb
A. G. Baydin
Andrew Markham
Stephen J. Roberts
43
32
0
14 Oct 2019
The Randomized Midpoint Method for Log-Concave Sampling
The Randomized Midpoint Method for Log-Concave Sampling
Ruoqi Shen
Y. Lee
89
115
0
12 Sep 2019
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of
  multi-step gradients
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients
Yuansi Chen
Raaz Dwivedi
Martin J. Wainwright
Bin Yu
46
101
0
29 May 2019
Pyro: Deep Universal Probabilistic Programming
Pyro: Deep Universal Probabilistic Programming
Eli Bingham
Jonathan P. Chen
M. Jankowiak
F. Obermeyer
Neeraj Pradhan
Theofanis Karaletsos
Rohit Singh
Paul A. Szerlip
Paul Horsfall
Noah D. Goodman
BDL
GP
155
1,053
0
18 Oct 2018
Log-concave sampling: Metropolis-Hastings algorithms are fast
Log-concave sampling: Metropolis-Hastings algorithms are fast
Raaz Dwivedi
Yuansi Chen
Martin J. Wainwright
Bin Yu
66
255
0
08 Jan 2018
Convergence Rate of Riemannian Hamiltonian Monte Carlo and Faster
  Polytope Volume Computation
Convergence Rate of Riemannian Hamiltonian Monte Carlo and Faster Polytope Volume Computation
Y. Lee
Santosh Vempala
58
113
0
17 Oct 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
82
298
0
12 Jul 2017
Stochastic Quasi-Newton Langevin Monte Carlo
Stochastic Quasi-Newton Langevin Monte Carlo
Umut Simsekli
Roland Badeau
A. Cemgil
G. Richard
BDL
47
62
0
10 Feb 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
162
4,297
0
18 Nov 2011
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