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A Complete Recipe for Stochastic Gradient MCMC
v1v2 (latest)

A Complete Recipe for Stochastic Gradient MCMC

15 June 2015
Yian Ma
Tianqi Chen
E. Fox
    BDLSyDa
ArXiv (abs)PDFHTML

Papers citing "A Complete Recipe for Stochastic Gradient MCMC"

15 / 165 papers shown
Title
Quasi-stationary Monte Carlo and the ScaLE Algorithm
Quasi-stationary Monte Carlo and the ScaLE Algorithm
M. Pollock
Paul Fearnhead
A. M. Johansen
Gareth O. Roberts
98
18
0
12 Sep 2016
Stochastic Bouncy Particle Sampler
Stochastic Bouncy Particle Sampler
Ari Pakman
D. Gilboa
David Carlson
Liam Paninski
96
32
0
03 Sep 2016
Softplus Regressions and Convex Polytopes
Softplus Regressions and Convex Polytopes
Mingyuan Zhou
75
16
0
23 Aug 2016
Ensemble preconditioning for Markov chain Monte Carlo simulation
Ensemble preconditioning for Markov chain Monte Carlo simulation
Charles Matthews
Jonathan Weare
Benedict Leimkuhler
62
57
0
13 Jul 2016
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
96
233
0
11 Jul 2016
Magnetic Hamiltonian Monte Carlo
Magnetic Hamiltonian Monte Carlo
Nilesh Tripuraneni
Mark Rowland
Zoubin Ghahramani
Richard Turner
48
37
0
10 Jul 2016
CaMKII activation supports reward-based neural network optimization
  through Hamiltonian sampling
CaMKII activation supports reward-based neural network optimization through Hamiltonian sampling
Zhaofei Yu
David Kappel
Robert Legenstein
Sen Song
Feng Chen
Wolfgang Maass
50
1
0
01 Jun 2016
Collaborative Filtering with Side Information: a Gaussian Process
  Perspective
Collaborative Filtering with Side Information: a Gaussian Process Perspective
Hyunjik Kim
Xiaoyu Lu
Seth Flaxman
Yee Whye Teh
32
3
0
23 May 2016
Patterns of Scalable Bayesian Inference
Patterns of Scalable Bayesian Inference
E. Angelino
Matthew J. Johnson
Ryan P. Adams
107
87
0
16 Feb 2016
Stochastic Quasi-Newton Langevin Monte Carlo
Stochastic Quasi-Newton Langevin Monte Carlo
Umut Simsekli
Roland Badeau
A. Cemgil
G. Richard
BDL
72
62
0
10 Feb 2016
A Variational Analysis of Stochastic Gradient Algorithms
A Variational Analysis of Stochastic Gradient Algorithms
Stephan Mandt
Matthew D. Hoffman
David M. Blei
68
161
0
08 Feb 2016
Variational Hamiltonian Monte Carlo via Score Matching
Variational Hamiltonian Monte Carlo via Score Matching
Cheng Zhang
Babak Shahbaba
Hongkai Zhao
BDL
70
26
0
06 Feb 2016
Distributed Bayesian Learning with Stochastic Natural-gradient
  Expectation Propagation and the Posterior Server
Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server
Leonard Hasenclever
Stefan Webb
Thibaut Lienart
Sebastian J. Vollmer
Balaji Lakshminarayanan
Charles Blundell
Yee Whye Teh
BDL
183
70
0
31 Dec 2015
High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep
  Models
High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models
Chunyuan Li
Changyou Chen
Kai Fan
Lawrence Carin
BDL
96
25
0
23 Dec 2015
Big Learning with Bayesian Methods
Big Learning with Bayesian Methods
Jun Zhu
Jianfei Chen
Wenbo Hu
Bo Zhang
BDL
531
84
0
24 Nov 2014
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