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. 1909.13339
  4. Cited By
MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy

MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy

29 September 2019
Badr-Eddine Chérief-Abdellatif
Pierre Alquier
ArXivPDFHTML

Papers citing "MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy"

29 / 29 papers shown
Title
Kernel Quantile Embeddings and Associated Probability Metrics
Kernel Quantile Embeddings and Associated Probability Metrics
Masha Naslidnyk
Siu Lun Chau
F. Briol
Krikamol Muandet
70
0
0
26 May 2025
Integral Imprecise Probability Metrics
Integral Imprecise Probability Metrics
Siu Lun Chau
Michele Caprio
Krikamol Muandet
96
0
0
22 May 2025
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
Arnaud Vadeboncoeur
O. Deniz Akyildiz
Ieva Kazlauskaite
Mark Girolami
PINN
99
0
0
10 Sep 2024
Continual learning with the neural tangent ensemble
Continual learning with the neural tangent ensemble
Ari S. Benjamin
Christian Pehle
Kyle Daruwalla
UQCV
122
1
0
30 Aug 2024
On the Robustness of Kernel Goodness-of-Fit Tests
On the Robustness of Kernel Goodness-of-Fit Tests
Xing Liu
F. Briol
OOD
99
5
0
11 Aug 2024
Targeted Separation and Convergence with Kernel Discrepancies
Targeted Separation and Convergence with Kernel Discrepancies
Alessandro Barp
Carl-Johann Simon-Gabriel
Mark Girolami
Lester W. Mackey
96
15
0
26 Sep 2022
Composite Goodness-of-fit Tests with Kernels
Composite Goodness-of-fit Tests with Kernels
Oscar Key
Arthur Gretton
F. Briol
T. Fernandez
78
16
0
19 Nov 2021
Convergence Rates of Variational Inference in Sparse Deep Learning
Convergence Rates of Variational Inference in Sparse Deep Learning
Badr-Eddine Chérief-Abdellatif
BDL
67
38
0
09 Aug 2019
Statistical Inference for Generative Models with Maximum Mean
  Discrepancy
Statistical Inference for Generative Models with Maximum Mean Discrepancy
François‐Xavier Briol
Alessandro Barp
Andrew B. Duncan
Mark Girolami
51
72
0
13 Jun 2019
PAC-Bayes under potentially heavy tails
PAC-Bayes under potentially heavy tails
Matthew J. Holland
79
42
0
20 May 2019
A Generalization Bound for Online Variational Inference
A Generalization Bound for Online Variational Inference
Badr-Eddine Chérief-Abdellatif
Pierre Alquier
Mohammad Emtiyaz Khan
BDL
38
26
0
08 Apr 2019
Consistency of ELBO maximization for model selection
Consistency of ELBO maximization for model selection
Badr-Eddine Chérief-Abdellatif
68
19
0
28 Oct 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
89
52
0
14 May 2018
Principles of Bayesian Inference using General Divergence Criteria
Principles of Bayesian Inference using General Divergence Criteria
Jack Jewson
Jim Q. Smith
Chris Holmes
53
88
0
26 Feb 2018
On Statistical Optimality of Variational Bayes
On Statistical Optimality of Variational Bayes
D. Pati
A. Bhattacharya
Yun Yang
52
64
0
25 Dec 2017
Robust Bayes-Like Estimation: Rho-Bayes estimation
Robust Bayes-Like Estimation: Rho-Bayes estimation
Y. Baraud
Lucien Birgé
39
4
0
22 Nov 2017
Variational Inference based on Robust Divergences
Variational Inference based on Robust Divergences
Futoshi Futami
Issei Sato
Masashi Sugiyama
BDL
OOD
78
67
0
18 Oct 2017
Probably approximate Bayesian computation: nonasymptotic convergence of
  ABC under misspecification
Probably approximate Bayesian computation: nonasymptotic convergence of ABC under misspecification
James Ridgway
58
8
0
19 Jul 2017
Concentration of tempered posteriors and of their variational
  approximations
Concentration of tempered posteriors and of their variational approximations
Pierre Alquier
James Ridgway
66
124
0
28 Jun 2017
Bayesian fractional posteriors
Bayesian fractional posteriors
A. Bhattacharya
D. Pati
Yun Yang
74
108
0
03 Nov 2016
Uncertain programming model for multi-item solid transportation problem
Uncertain programming model for multi-item solid transportation problem
Hasan Dalman
104
735
0
31 May 2016
Minimax Estimation of Kernel Mean Embeddings
Minimax Estimation of Kernel Mean Embeddings
Ilya O. Tolstikhin
Bharath K. Sriperumbudur
Krikamol Muandet
47
86
0
13 Feb 2016
On the properties of variational approximations of Gibbs posteriors
On the properties of variational approximations of Gibbs posteriors
Pierre Alquier
James Ridgway
Nicolas Chopin
102
255
0
12 Jun 2015
Training generative neural networks via Maximum Mean Discrepancy
  optimization
Training generative neural networks via Maximum Mean Discrepancy optimization
Gintare Karolina Dziugaite
Daniel M. Roy
Zoubin Ghahramani
GAN
84
530
0
14 May 2015
Generative Moment Matching Networks
Generative Moment Matching Networks
Yujia Li
Kevin Swersky
R. Zemel
OOD
GAN
105
847
0
10 Feb 2015
Inconsistency of Bayesian Inference for Misspecified Linear Models, and
  a Proposal for Repairing It
Inconsistency of Bayesian Inference for Misspecified Linear Models, and a Proposal for Repairing It
Peter Grünwald
T. V. Ommen
86
267
0
11 Dec 2014
A General Framework for Updating Belief Distributions
A General Framework for Updating Belief Distributions
Pier Giovanni Bissiri
Chris Holmes
S. Walker
216
476
0
27 Jun 2013
Challenging the empirical mean and empirical variance: a deviation study
Challenging the empirical mean and empirical variance: a deviation study
O. Catoni
166
462
0
10 Sep 2010
Pac-Bayesian Supervised Classification: The Thermodynamics of
  Statistical Learning
Pac-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning
O. Catoni
306
458
0
03 Dec 2007
1