ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1705.03439
  4. Cited By
Frequentist Consistency of Variational Bayes

Frequentist Consistency of Variational Bayes

9 May 2017
Yixin Wang
David M. Blei
    BDL
ArXivPDFHTML

Papers citing "Frequentist Consistency of Variational Bayes"

29 / 29 papers shown
Title
Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix
Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix
C. Margossian
Lawrence K. Saul
31
1
0
14 Oct 2024
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling
Alex Glyn-Davies
A. Vadeboncoeur
O. Deniz Akyildiz
Ieva Kazlauskaite
Mark Girolami
PINN
67
0
0
10 Sep 2024
posteriordb: Testing, Benchmarking and Developing Bayesian Inference
  Algorithms
posteriordb: Testing, Benchmarking and Developing Bayesian Inference Algorithms
Måns Magnusson
Jakob Torgander
Paul-Christian Burkner
Lu Zhang
Bob Carpenter
Aki Vehtari
42
6
0
06 Jul 2024
Simplifying Deep Temporal Difference Learning
Simplifying Deep Temporal Difference Learning
Matteo Gallici
Mattie Fellows
Benjamin Ellis
B. Pou
Ivan Masmitja
Jakob Foerster
Mario Martin
OffRL
59
14
0
05 Jul 2024
Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs
Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs
C. Margossian
Loucas Pillaud-Vivien
Lawrence K. Saul
UD
71
2
0
20 Mar 2024
Machine Learning and the Future of Bayesian Computation
Machine Learning and the Future of Bayesian Computation
Steven Winter
Trevor Campbell
Lizhen Lin
Sanvesh Srivastava
David B. Dunson
TPM
39
4
0
21 Apr 2023
An Adaptive Kernel Approach to Federated Learning of Heterogeneous
  Causal Effects
An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects
Thanh Vinh Vo
Arnab Bhattacharyya
Young Lee
Tze-Yun Leong
FedML
16
19
0
01 Jan 2023
Uncertainty quantification for sparse spectral variational
  approximations in Gaussian process regression
Uncertainty quantification for sparse spectral variational approximations in Gaussian process regression
D. Nieman
Botond Szabó
Harry Van Zanten
23
5
0
21 Dec 2022
Generalization Gap in Amortized Inference
Generalization Gap in Amortized Inference
Mingtian Zhang
Peter Hayes
David Barber
BDL
CML
DRL
40
14
0
23 May 2022
On the inability of Gaussian process regression to optimally learn
  compositional functions
On the inability of Gaussian process regression to optimally learn compositional functions
M. Giordano
Kolyan Ray
Johannes Schmidt-Hieber
33
12
0
16 May 2022
Bayesian Nonlinear Models for Repeated Measurement Data: An Overview,
  Implementation, and Applications
Bayesian Nonlinear Models for Repeated Measurement Data: An Overview, Implementation, and Applications
Se Yoon Lee
17
18
0
28 Jan 2022
Approximating Bayes in the 21st Century
Approximating Bayes in the 21st Century
G. Martin
David T. Frazier
Christian P. Robert
36
26
0
20 Dec 2021
Variational Bayesian Approximation of Inverse Problems using Sparse
  Precision Matrices
Variational Bayesian Approximation of Inverse Problems using Sparse Precision Matrices
Jan Povala
Ieva Kazlauskaite
Eky Febrianto
F. Cirak
Mark Girolami
26
22
0
22 Oct 2021
Desiderata for Representation Learning: A Causal Perspective
Desiderata for Representation Learning: A Causal Perspective
Yixin Wang
Michael I. Jordan
CML
32
80
0
08 Sep 2021
Black Box Variational Bayesian Model Averaging
Black Box Variational Bayesian Model Averaging
Vojtech Kejzlar
Shrijita Bhattacharya
Mookyong Son
T. Maiti
BDL
16
3
0
23 Jun 2021
Variational Bayes in State Space Models: Inferential and Predictive
  Accuracy
Variational Bayes in State Space Models: Inferential and Predictive Accuracy
David T. Frazier
Rubén Loaiza-Maya
G. Martin
11
13
0
23 Jun 2021
The computational asymptotics of Gaussian variational inference and the
  Laplace approximation
The computational asymptotics of Gaussian variational inference and the Laplace approximation
Zuheng Xu
Trevor Campbell
19
7
0
13 Apr 2021
PAC-Bayes Bounds on Variational Tempered Posteriors for Markov Models
PAC-Bayes Bounds on Variational Tempered Posteriors for Markov Models
Imon Banerjee
Vinayak A. Rao
Harsha Honnappa
19
11
0
13 Jan 2021
Spike and slab variational Bayes for high dimensional logistic
  regression
Spike and slab variational Bayes for high dimensional logistic regression
Kolyan Ray
Botond Szabó
Gabriel Clara
35
28
0
22 Oct 2020
Statistical Guarantees and Algorithmic Convergence Issues of Variational
  Boosting
Statistical Guarantees and Algorithmic Convergence Issues of Variational Boosting
B. Guha
A. Bhattacharya
D. Pati
26
2
0
19 Oct 2020
Dynamics of coordinate ascent variational inference: A case study in 2D
  Ising models
Dynamics of coordinate ascent variational inference: A case study in 2D Ising models
Sean Plummer
D. Pati
A. Bhattacharya
28
18
0
13 Jul 2020
Variational Inference with Vine Copulas: An efficient Approach for
  Bayesian Computer Model Calibration
Variational Inference with Vine Copulas: An efficient Approach for Bayesian Computer Model Calibration
Vojtech Kejzlar
T. Maiti
8
6
0
28 Mar 2020
An end-to-end Differentially Private Latent Dirichlet Allocation Using a
  Spectral Algorithm
An end-to-end Differentially Private Latent Dirichlet Allocation Using a Spectral Algorithm
Christopher DeCarolis
Mukul Ram
Seyed-Alireza Esmaeili
Yu-Xiang Wang
Furong Huang
FedML
4
12
0
25 May 2018
Consistency of Variational Bayes Inference for Estimation and Model
  Selection in Mixtures
Consistency of Variational Bayes Inference for Estimation and Model Selection in Mixtures
Badr-Eddine Chérief-Abdellatif
Pierre Alquier
35
52
0
14 May 2018
Gaussian variational approximation for high-dimensional state space
  models
Gaussian variational approximation for high-dimensional state space models
M. Quiroz
David J. Nott
Robert Kohn
16
41
0
24 Jan 2018
Advances in Variational Inference
Advances in Variational Inference
Cheng Zhang
Judith Butepage
Hedvig Kjellström
Stephan Mandt
BDL
38
684
0
15 Nov 2017
Concentration of tempered posteriors and of their variational
  approximations
Concentration of tempered posteriors and of their variational approximations
Pierre Alquier
James Ridgway
27
121
0
28 Jun 2017
Asymptotic normality of maximum likelihood and its variational
  approximation for stochastic blockmodels
Asymptotic normality of maximum likelihood and its variational approximation for stochastic blockmodels
Peter J. Bickel
David S. Choi
Xiangyu Chang
Hai Zhang
65
220
0
04 Jul 2012
A Bernstein-Von Mises Theorem for discrete probability distributions
A Bernstein-Von Mises Theorem for discrete probability distributions
S. Boucheron
Elisabeth Gassiat
103
49
0
14 Jul 2008
1