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Principles of Bayesian Inference using General Divergence Criteria
v1v2 (latest)

Principles of Bayesian Inference using General Divergence Criteria

26 February 2018
Jack Jewson
Jim Q. Smith
Chris Holmes
ArXiv (abs)PDFHTML

Papers citing "Principles of Bayesian Inference using General Divergence Criteria"

36 / 36 papers shown
Title
Decision Making under Model Misspecification: DRO with Robust Bayesian Ambiguity Sets
Decision Making under Model Misspecification: DRO with Robust Bayesian Ambiguity Sets
Charita Dellaporta
Patrick O'Hara
Theodoros Damoulas
119
0
0
06 May 2025
Correcting Mode Proportion Bias in Generalized Bayesian Inference via a Weighted Kernel Stein Discrepancy
Elham Afzali
Saman Muthukumarana
Liqun Wang
91
0
0
03 Mar 2025
Misspecification-robust likelihood-free inference in high dimensions
Misspecification-robust likelihood-free inference in high dimensions
Owen Thomas
Raquel Sá-Leao
H. Lencastre
Samuel Kaski
J. Corander
Henri Pesonen
242
9
0
17 Feb 2025
Predictive performance of power posteriors
Predictive performance of power posteriors
Yann McLatchie
Edwin Fong
David T. Frazier
Jeremias Knoblauch
61
2
0
16 Aug 2024
Generalised Bayes Linear Inference
Generalised Bayes Linear Inference
L. Astfalck
Cassandra Bird
Daniel Williamson
AI4CE
62
0
0
23 May 2024
GAD-PVI: A General Accelerated Dynamic-Weight Particle-Based Variational
  Inference Framework
GAD-PVI: A General Accelerated Dynamic-Weight Particle-Based Variational Inference Framework
Fangyikang Wang
Huminhao Zhu
Chao Zhang
Han Zhao
Hui Qian
81
8
0
27 Dec 2023
Reproducible Parameter Inference Using Bagged Posteriors
Reproducible Parameter Inference Using Bagged Posteriors
Jonathan H. Huggins
Jeffrey W. Miller
UQCV
128
1
0
03 Nov 2023
An Introduction to the Calibration of Computer Models
An Introduction to the Calibration of Computer Models
Richard D. Wilkinson
Christopher W. Lanyon
52
0
0
13 Oct 2023
On the meaning of uncertainty for ethical AI: philosophy and practice
On the meaning of uncertainty for ethical AI: philosophy and practice
Cassandra Bird
Daniel Williamson
Sabina Leonelli
37
1
0
11 Sep 2023
Differentially Private Statistical Inference through $β$-Divergence
  One Posterior Sampling
Differentially Private Statistical Inference through βββ-Divergence One Posterior Sampling
Jack Jewson
Sahra Ghalebikesabi
Chris Holmes
84
2
0
11 Jul 2023
A Rigorous Link between Deep Ensembles and (Variational) Bayesian
  Methods
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods
Veit Wild
Sahra Ghalebikesabi
Dino Sejdinovic
Jeremias Knoblauch
BDLUQCV
98
16
0
24 May 2023
Robustness of Bayesian ordinal response model against outliers via
  divergence approach
Robustness of Bayesian ordinal response model against outliers via divergence approach
Tomotaka Momozaki
Tomoyuki Nakagawa
60
1
0
12 May 2023
Robustifying likelihoods by optimistically re-weighting data
Robustifying likelihoods by optimistically re-weighting data
Miheer Dewaskar
Christopher Tosh
Jeremias Knoblauch
David B. Dunson
93
6
0
19 Mar 2023
A Semi-Bayesian Nonparametric Estimator of the Maximum Mean Discrepancy
  Measure: Applications in Goodness-of-Fit Testing and Generative Adversarial
  Networks
A Semi-Bayesian Nonparametric Estimator of the Maximum Mean Discrepancy Measure: Applications in Goodness-of-Fit Testing and Generative Adversarial Networks
Forough Fazeli Asl
M. Zhang
Lizhen Lin
77
1
0
05 Mar 2023
A view on model misspecification in uncertainty quantification
A view on model misspecification in uncertainty quantification
Yuko Kato
David Tax
Marco Loog
62
3
0
30 Oct 2022
Sampling algorithms in statistical physics: a guide for statistics and
  machine learning
Sampling algorithms in statistical physics: a guide for statistics and machine learning
Michael F Faulkner
Samuel Livingstone
57
7
0
09 Aug 2022
Robust Bayesian Learning for Reliable Wireless AI: Framework and
  Applications
Robust Bayesian Learning for Reliable Wireless AI: Framework and Applications
Matteo Zecchin
Sangwoo Park
Osvaldo Simeone
Marios Kountouris
David Gesbert
78
15
0
01 Jul 2022
Concentration of discrepancy-based approximate Bayesian computation via
  Rademacher complexity
Concentration of discrepancy-based approximate Bayesian computation via Rademacher complexity
Sirio Legramanti
Daniele Durante
Pierre Alquier
98
6
0
14 Jun 2022
Robust PAC$^m$: Training Ensemble Models Under Misspecification and
  Outliers
Robust PACm^mm: Training Ensemble Models Under Misspecification and Outliers
Matteo Zecchin
Sangwoo Park
Osvaldo Simeone
Marios Kountouris
David Gesbert
95
5
0
03 Mar 2022
Adaptation of the Tuning Parameter in General Bayesian Inference with
  Robust Divergence
Adaptation of the Tuning Parameter in General Bayesian Inference with Robust Divergence
S. Yonekura
S. Sugasawa
124
25
0
13 Jun 2021
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
80
80
0
15 Apr 2021
Introducing prior information in Weighted Likelihood Bootstrap with
  applications to model misspecification
Introducing prior information in Weighted Likelihood Bootstrap with applications to model misspecification
E. Pompe
124
9
0
26 Mar 2021
Generalized Posteriors in Approximate Bayesian Computation
Generalized Posteriors in Approximate Bayesian Computation
Sebastian M. Schmon
Patrick W Cannon
Jeremias Knoblauch
111
25
0
17 Nov 2020
Foundations of Bayesian Learning from Synthetic Data
Foundations of Bayesian Learning from Synthetic Data
H. Wilde
Jack Jewson
Sebastian J. Vollmer
Chris Holmes
87
15
0
16 Nov 2020
Robust Bayesian Inference for Discrete Outcomes with the Total Variation
  Distance
Robust Bayesian Inference for Discrete Outcomes with the Total Variation Distance
Jeremias Knoblauch
Lara Vomfell
72
7
0
26 Oct 2020
$β$-Cores: Robust Large-Scale Bayesian Data Summarization in the
  Presence of Outliers
βββ-Cores: Robust Large-Scale Bayesian Data Summarization in the Presence of Outliers
Dionysis Manousakas
Cecilia Mascolo
45
2
0
31 Aug 2020
Finite mixture models do not reliably learn the number of components
Finite mixture models do not reliably learn the number of components
Diana Cai
Trevor Campbell
Tamara Broderick
66
23
0
08 Jul 2020
Robust Bayesian Classification Using an Optimistic Score Ratio
Robust Bayesian Classification Using an Optimistic Score Ratio
Viet Anh Nguyen
Nian Si
Jose H. Blanchet
84
13
0
08 Jul 2020
Generalised Bayes Updates with $f$-divergences through Probabilistic
  Classifiers
Generalised Bayes Updates with fff-divergences through Probabilistic Classifiers
Owen Thomas
Henri Pesonen
J. Corander
FedML
65
2
0
08 Jul 2020
Generalized Bayesian Filtering via Sequential Monte Carlo
Generalized Bayesian Filtering via Sequential Monte Carlo
Ayman Boustati
Ömer Deniz Akyildiz
Theodoros Damoulas
A. M. Johansen
67
4
0
23 Feb 2020
Frequentist Consistency of Generalized Variational Inference
Frequentist Consistency of Generalized Variational Inference
Jeremias Knoblauch
66
11
0
10 Dec 2019
On Robust Pseudo-Bayes Estimation for the Independent Non-homogeneous
  Set-up
On Robust Pseudo-Bayes Estimation for the Independent Non-homogeneous Set-up
Tuhin Majumder
A. Basu
A. Ghosh
44
0
0
27 Nov 2019
MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy
MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy
Badr-Eddine Chérief-Abdellatif
Pierre Alquier
186
75
0
29 Sep 2019
Robust Deep Gaussian Processes
Robust Deep Gaussian Processes
Jeremias Knoblauch
GP
62
17
0
04 Apr 2019
Generalized Variational Inference: Three arguments for deriving new
  Posteriors
Generalized Variational Inference: Three arguments for deriving new Posteriors
Jeremias Knoblauch
Jack Jewson
Theodoros Damoulas
DRLBDL
109
106
0
03 Apr 2019
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with
  $β$-Divergences
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with βββ-Divergences
Jeremias Knoblauch
Jack Jewson
Theodoros Damoulas
81
58
0
06 Jun 2018
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