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Geometry and Dynamics for Markov Chain Monte Carlo

Geometry and Dynamics for Markov Chain Monte Carlo

8 May 2017
Alessandro Barp
François‐Xavier Briol
A. Kennedy
Mark Girolami
    AI4CE
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Papers citing "Geometry and Dynamics for Markov Chain Monte Carlo"

19 / 19 papers shown
Title
On the Convergence of Stochastic Gradient MCMC Algorithms with
  High-Order Integrators
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators
Changyou Chen
Nan Ding
Lawrence Carin
69
161
0
21 Oct 2016
Geometric MCMC for Infinite-Dimensional Inverse Problems
Geometric MCMC for Infinite-Dimensional Inverse Problems
A. Beskos
Mark Girolami
Shiwei Lan
P. Farrell
Andrew M. Stuart
48
143
0
20 Jun 2016
Geometrically Tempered Hamiltonian Monte Carlo
Geometrically Tempered Hamiltonian Monte Carlo
A. Nishimura
David B. Dunson
30
22
0
04 Apr 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
89
116
0
29 Jan 2016
Emulation of Higher-Order Tensors in Manifold Monte Carlo Methods for
  Bayesian Inverse Problems
Emulation of Higher-Order Tensors in Manifold Monte Carlo Methods for Bayesian Inverse Problems
Shiwei Lan
T. Bui-Thanh
M. Christie
Mark Girolami
58
58
0
22 Jul 2015
A Complete Recipe for Stochastic Gradient MCMC
A Complete Recipe for Stochastic Gradient MCMC
Yian Ma
Tianqi Chen
E. Fox
BDL
SyDa
62
486
0
15 Jun 2015
(Non-) asymptotic properties of Stochastic Gradient Langevin Dynamics
(Non-) asymptotic properties of Stochastic Gradient Langevin Dynamics
Sebastian J. Vollmer
K. Zygalakis
and Yee Whye Teh
78
49
0
02 Jan 2015
Consistency and fluctuations for stochastic gradient Langevin dynamics
Consistency and fluctuations for stochastic gradient Langevin dynamics
Yee Whye Teh
Alexandre Hoang Thiery
Sebastian J. Vollmer
66
234
0
01 Sep 2014
Solving Large-Scale PDE-constrained Bayesian Inverse Problems with
  Riemann Manifold Hamiltonian Monte Carlo
Solving Large-Scale PDE-constrained Bayesian Inverse Problems with Riemann Manifold Hamiltonian Monte Carlo
T. Bui-Thanh
Mark Girolami
51
70
0
06 Jul 2014
Information-geometric Markov Chain Monte Carlo methods using Diffusions
Information-geometric Markov Chain Monte Carlo methods using Diffusions
Samuel Livingstone
Mark Girolami
DiffM
96
45
0
31 Mar 2014
Compressible Generalized Hybrid Monte Carlo
Compressible Generalized Hybrid Monte Carlo
Youhan Fang
J. Sanz-Serna
R. Skeel
68
61
0
28 Feb 2014
Stochastic Gradient Hamiltonian Monte Carlo
Stochastic Gradient Hamiltonian Monte Carlo
Tianqi Chen
E. Fox
Carlos Guestrin
BDL
106
910
0
17 Feb 2014
Wormhole Hamiltonian Monte Carlo
Wormhole Hamiltonian Monte Carlo
Shiwei Lan
J. Streets
Babak Shahbaba
89
65
0
01 Jun 2013
Adaptive Hamiltonian and Riemann Manifold Monte Carlo Samplers
Adaptive Hamiltonian and Riemann Manifold Monte Carlo Samplers
Ziyun Wang
S. Mohamed
Nando de Freitas
152
56
0
25 Feb 2013
Geodesic Monte Carlo on Embedded Manifolds
Geodesic Monte Carlo on Embedded Manifolds
Simon Byrne
Mark Girolami
96
152
0
25 Jan 2013
Lagrangian Dynamical Monte Carlo
Lagrangian Dynamical Monte Carlo
Shiwei Lan
V. Stathopoulos
Babak Shahbaba
Mark Girolami
88
46
0
15 Nov 2012
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
290
3,281
0
09 Jun 2012
MCMC Methods for Functions: Modifying Old Algorithms to Make Them Faster
MCMC Methods for Functions: Modifying Old Algorithms to Make Them Faster
S. Cotter
Gareth O. Roberts
Andrew M. Stuart
D. White
97
480
0
03 Feb 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
165
4,300
0
18 Nov 2011
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