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Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential
  Families
v1v2 (latest)

Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families

8 June 2015
Heiko Strathmann
Dino Sejdinovic
Samuel Livingstone
Z. Szabó
Arthur Gretton
    BDL
ArXiv (abs)PDFHTML

Papers citing "Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families"

29 / 29 papers shown
Title
Energy-Guided Continuous Entropic Barycenter Estimation for General Costs
Energy-Guided Continuous Entropic Barycenter Estimation for General Costs
Alexander Kolesov
Petr Mokrov
Igor Udovichenko
Milena Gazdieva
G. Pammer
Anastasis Kratsios
Evgeny Burnaev
Alexander Korotin
OT
133
3
0
02 Oct 2023
Differentiable Neural Networks with RePU Activation: with Applications
  to Score Estimation and Isotonic Regression
Differentiable Neural Networks with RePU Activation: with Applications to Score Estimation and Isotonic Regression
Guohao Shen
Yuling Jiao
Yuanyuan Lin
Jian Huang
129
3
0
01 May 2023
Robust Generalised Bayesian Inference for Intractable Likelihoods
Robust Generalised Bayesian Inference for Intractable Likelihoods
Takuo Matsubara
Jeremias Knoblauch
François‐Xavier Briol
Chris J. Oates
UQCV
87
80
0
15 Apr 2021
Ensemble Inference Methods for Models With Noisy and Expensive
  Likelihoods
Ensemble Inference Methods for Models With Noisy and Expensive Likelihoods
Oliver R. A. Dunbar
Andrew B. Duncan
Andrew M. Stuart
Marie-Therese Wolfram
82
27
0
07 Apr 2021
Efficient Learning of Generative Models via Finite-Difference Score
  Matching
Efficient Learning of Generative Models via Finite-Difference Score Matching
Tianyu Pang
Kun Xu
Chongxuan Li
Yang Song
Stefano Ermon
Jun Zhu
DiffM
104
55
0
07 Jul 2020
Nonparametric Score Estimators
Nonparametric Score Estimators
Yuhao Zhou
Jiaxin Shi
Jun Zhu
106
24
0
20 May 2020
Kernelized Wasserstein Natural Gradient
Kernelized Wasserstein Natural Gradient
Michael Arbel
Arthur Gretton
Wuchen Li
Guido Montúfar
70
23
0
21 Oct 2019
Deep Markov Chain Monte Carlo
Deep Markov Chain Monte Carlo
Babak Shahbaba
L. M. Lomeli
T. Chen
Shiwei Lan
BDL
66
8
0
13 Oct 2019
Walsh-Hadamard Variational Inference for Bayesian Deep Learning
Walsh-Hadamard Variational Inference for Bayesian Deep Learning
Simone Rossi
Sébastien Marmin
Maurizio Filippone
BDL
110
16
0
27 May 2019
Sliced Score Matching: A Scalable Approach to Density and Score
  Estimation
Sliced Score Matching: A Scalable Approach to Density and Score Estimation
Yang Song
Sahaj Garg
Jiaxin Shi
Stefano Ermon
171
419
0
17 May 2019
Efficiency and robustness in Monte Carlo sampling of 3-D geophysical
  inversions with Obsidian v0.1.2: Setting up for success
Efficiency and robustness in Monte Carlo sampling of 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success
R. Scalzo
D. Kohn
H. Olierook
G. Houseman
Rohitash Chandra
Mark Girolami
Sally Cripps
67
32
0
02 Dec 2018
Learning deep kernels for exponential family densities
Learning deep kernels for exponential family densities
W. Li
Danica J. Sutherland
Heiko Strathmann
Arthur Gretton
BDL
106
74
0
20 Nov 2018
A Spectral Approach to Gradient Estimation for Implicit Distributions
A Spectral Approach to Gradient Estimation for Implicit Distributions
Jiaxin Shi
Shengyang Sun
Jun Zhu
108
92
0
07 Jun 2018
Stein Variational Gradient Descent Without Gradient
Stein Variational Gradient Descent Without Gradient
J. Han
Qiang Liu
92
45
0
07 Jun 2018
Generalizing Hamiltonian Monte Carlo with Neural Networks
Generalizing Hamiltonian Monte Carlo with Neural Networks
Daniel Levy
Matthew D. Hoffman
Jascha Narain Sohl-Dickstein
BDL
92
130
0
25 Nov 2017
Kernel Conditional Exponential Family
Kernel Conditional Exponential Family
Michael Arbel
Arthur Gretton
90
26
0
15 Nov 2017
Modified Hamiltonian Monte Carlo for Bayesian inference
Modified Hamiltonian Monte Carlo for Bayesian inference
Tijana Radivojević
E. Akhmatskaya
122
31
0
13 Jun 2017
Kinetic energy choice in Hamiltonian/hybrid Monte Carlo
Kinetic energy choice in Hamiltonian/hybrid Monte Carlo
Samuel Livingstone
Michael F Faulkner
Gareth O. Roberts
105
45
0
08 Jun 2017
Hamiltonian Monte Carlo Methods for Subset Simulation in Reliability
  Analysis
Hamiltonian Monte Carlo Methods for Subset Simulation in Reliability Analysis
Ziqi Wang
M. Broccardo
Junho Song
46
123
0
05 Jun 2017
Gradient Estimators for Implicit Models
Gradient Estimators for Implicit Models
Yingzhen Li
Richard Turner
174
108
0
19 May 2017
Pseudo-Marginal Hamiltonian Monte Carlo
Pseudo-Marginal Hamiltonian Monte Carlo
Johan Alenlöv
Arnaud Doucet
Fredrik Lindsten
89
22
0
08 Jul 2016
Uncertain programming model for multi-item solid transportation problem
Uncertain programming model for multi-item solid transportation problem
Hasan Dalman
170
64
0
31 May 2016
A Kernel Test of Goodness of Fit
A Kernel Test of Goodness of Fit
Kacper P. Chwialkowski
Heiko Strathmann
Arthur Gretton
BDL
219
328
0
09 Feb 2016
Variational Hamiltonian Monte Carlo via Score Matching
Variational Hamiltonian Monte Carlo via Score Matching
Cheng Zhang
Babak Shahbaba
Hongkai Zhao
BDL
95
26
0
06 Feb 2016
Kernel Sequential Monte Carlo
Kernel Sequential Monte Carlo
Ingmar Schuster
Heiko Strathmann
Brooks Paige
Dino Sejdinovic
BDL
84
7
0
11 Oct 2015
Hamiltonian Monte Carlo Acceleration Using Surrogate Functions with
  Random Bases
Hamiltonian Monte Carlo Acceleration Using Surrogate Functions with Random Bases
Cheng Zhang
Babak Shahbaba
Hongkai Zhao
155
32
0
18 Jun 2015
Optimal Rates for Random Fourier Features
Optimal Rates for Random Fourier Features
Bharath K. Sriperumbudur
Z. Szabó
108
130
0
06 Jun 2015
Scalable Bayesian Inference for the Inverse Temperature of a Hidden
  Potts Model
Scalable Bayesian Inference for the Inverse Temperature of a Hidden Potts Model
M. Moores
Geoff K. Nicholls
A. Pettitt
Kerrie Mengersen
TPM
187
22
0
27 Mar 2015
Density Estimation in Infinite Dimensional Exponential Families
Density Estimation in Infinite Dimensional Exponential Families
Bharath K. Sriperumbudur
Kenji Fukumizu
Arthur Gretton
Aapo Hyvarinen
Revant Kumar
98
128
0
12 Dec 2013
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