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A Unified Perspective on Natural Gradient Variational Inference with
  Gaussian Mixture Models
v1v2 (latest)

A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models

23 September 2022
Oleg Arenz
Philipp Dahlinger
Zihan Ye
Michael Volpp
Gerhard Neumann
ArXiv (abs)PDFHTML

Papers citing "A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models"

27 / 27 papers shown
Title
Learned Reference-based Diffusion Sampling for multi-modal distributions
Learned Reference-based Diffusion Sampling for multi-modal distributions
Maxence Noble
Louis Grenioux
Marylou Gabrié
Alain Durmus
DiffM
82
6
0
25 Oct 2024
NETS: A Non-Equilibrium Transport Sampler
NETS: A Non-Equilibrium Transport Sampler
M. S. Albergo
Eric Vanden-Eijnden
DiffM
104
21
0
03 Oct 2024
Monotonic Alpha-divergence Minimisation for Variational Inference
Monotonic Alpha-divergence Minimisation for Variational Inference
Kamélia Daudel
Randal Douc
François Roueff
65
9
0
09 Mar 2021
Tractable structured natural gradient descent using local
  parameterizations
Tractable structured natural gradient descent using local parameterizations
Wu Lin
Frank Nielsen
Mohammad Emtiyaz Khan
Mark Schmidt
57
30
0
15 Feb 2021
Differentiable Trust Region Layers for Deep Reinforcement Learning
Differentiable Trust Region Layers for Deep Reinforcement Learning
Fabian Otto
P. Becker
Ngo Anh Vien
Hanna Ziesche
Gerhard Neumann
OffRL
65
19
0
22 Jan 2021
Assisted Teleoperation in Changing Environments with a Mixture of
  Virtual Guides
Assisted Teleoperation in Changing Environments with a Mixture of Virtual Guides
Marco Ewerton
Oleg Arenz
Jan Peters
11
18
0
12 Aug 2020
Automatic Differentiation Variational Inference with Mixtures
Automatic Differentiation Variational Inference with Mixtures
Warren Morningstar
Sharad M. Vikram
Cusuh Ham
Andrew Gallagher
Joshua V. Dillon
DRLBDL
41
20
0
03 Mar 2020
Handling the Positive-Definite Constraint in the Bayesian Learning Rule
Handling the Positive-Definite Constraint in the Bayesian Learning Rule
Wu Lin
Mark Schmidt
Mohammad Emtiyaz Khan
BDL
73
36
0
24 Feb 2020
Expected Information Maximization: Using the I-Projection for Mixture
  Density Estimation
Expected Information Maximization: Using the I-Projection for Mixture Density Estimation
P. Becker
Oleg Arenz
Gerhard Neumann
23
16
0
23 Jan 2020
Stein's Lemma for the Reparameterization Trick with Exponential Family Mixtures
Stein's Lemma for the Reparameterization Trick with Exponential Family Mixtures
Wu Lin
Mohammad Emtiyaz Khan
Mark Schmidt
71
31
0
29 Oct 2019
Trust-Region Variational Inference with Gaussian Mixture Models
Trust-Region Variational Inference with Gaussian Mixture Models
Oleg Arenz
Mingjun Zhong
Gerhard Neumann
59
20
0
10 Jul 2019
Fast and Simple Natural-Gradient Variational Inference with Mixture of
  Exponential-family Approximations
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations
Wu Lin
Mohammad Emtiyaz Khan
Mark Schmidt
BDL
47
70
0
07 Jun 2019
Compatible Natural Gradient Policy Search
Compatible Natural Gradient Policy Search
Joni Pajarinen
Hong Linh Thai
R. Akrour
Jan Peters
Gerhard Neumann
41
22
0
07 Feb 2019
Fast yet Simple Natural-Gradient Descent for Variational Inference in
  Complex Models
Fast yet Simple Natural-Gradient Descent for Variational Inference in Complex Models
Mohammad Emtiyaz Khan
Didrik Nielsen
BDL
77
63
0
12 Jul 2018
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Mohammad Emtiyaz Khan
Didrik Nielsen
Voot Tangkaratt
Wu Lin
Y. Gal
Akash Srivastava
ODL
149
272
0
13 Jun 2018
Natural Gradients in Practice: Non-Conjugate Variational Inference in
  Gaussian Process Models
Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models
Hugh Salimbeni
Stefanos Eleftheriadis
J. Hensman
BDL
73
86
0
24 Mar 2018
Fast Black-box Variational Inference through Stochastic Trust-Region
  Optimization
Fast Black-box Variational Inference through Stochastic Trust-Region Optimization
Jeffrey Regier
Michael I. Jordan
Jon D. McAuliffe
34
28
0
07 Jun 2017
Sticking the Landing: Simple, Lower-Variance Gradient Estimators for
  Variational Inference
Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference
Geoffrey Roeder
Yuhuai Wu
David Duvenaud
BDL
112
201
0
27 Mar 2017
Conjugate-Computation Variational Inference : Converting Variational
  Inference in Non-Conjugate Models to Inferences in Conjugate Models
Conjugate-Computation Variational Inference : Converting Variational Inference in Non-Conjugate Models to Inferences in Conjugate Models
Mohammad Emtiyaz Khan
Wu Lin
BDL
51
137
0
13 Mar 2017
Variational Boosting: Iteratively Refining Posterior Approximations
Variational Boosting: Iteratively Refining Posterior Approximations
Andrew C. Miller
N. Foti
Ryan P. Adams
51
125
0
20 Nov 2016
Boosting Variational Inference
Boosting Variational Inference
Fangjian Guo
Xiangyu Wang
Kai Fan
Tamara Broderick
David B. Dunson
BDL
113
76
0
17 Nov 2016
Faster Stochastic Variational Inference using Proximal-Gradient Methods
  with General Divergence Functions
Faster Stochastic Variational Inference using Proximal-Gradient Methods with General Divergence Functions
Mohammad Emtiyaz Khan
Reza Babanezhad
Wu Lin
Mark Schmidt
Masashi Sugiyama
61
50
0
31 Oct 2015
A trust-region method for stochastic variational inference with
  applications to streaming data
A trust-region method for stochastic variational inference with applications to streaming data
Lucas Theis
Matthew D. Hoffman
53
43
0
28 May 2015
Trust Region Policy Optimization
Trust Region Policy Optimization
John Schulman
Sergey Levine
Philipp Moritz
Michael I. Jordan
Pieter Abbeel
277
6,776
0
19 Feb 2015
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
452
16,929
0
20 Dec 2013
Stochastic Variational Inference
Stochastic Variational Inference
Matt Hoffman
David M. Blei
Chong-Jun Wang
John Paisley
BDL
259
2,625
0
29 Jun 2012
Nonparametric variational inference
Nonparametric variational inference
S. Gershman
Matt Hoffman
David M. Blei
BDL
104
154
0
18 Jun 2012
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