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A General Framework for Updating Belief Distributions
v1v2 (latest)

A General Framework for Updating Belief Distributions

27 June 2013
Pier Giovanni Bissiri
Chris Holmes
S. Walker
ArXiv (abs)PDFHTML

Papers citing "A General Framework for Updating Belief Distributions"

50 / 204 papers shown
Title
Loss-calibrated expectation propagation for approximate Bayesian
  decision-making
Loss-calibrated expectation propagation for approximate Bayesian decision-making
Michael J. Morais
Jonathan W. Pillow
82
6
0
10 Jan 2022
Approximating Bayes in the 21st Century
Approximating Bayes in the 21st Century
G. Martin
David T. Frazier
Christian P. Robert
77
26
0
20 Dec 2021
Approximate Bayesian Computation via Classification
Approximate Bayesian Computation via Classification
Yuexi Wang
Tetsuya Kaji
Veronika Rockova
53
4
0
22 Nov 2021
User-friendly introduction to PAC-Bayes bounds
User-friendly introduction to PAC-Bayes bounds
Pierre Alquier
FedML
193
207
0
21 Oct 2021
Asymptotics of cut distributions and robust modular inference using
  Posterior Bootstrap
Asymptotics of cut distributions and robust modular inference using Posterior Bootstrap
E. Pompe
Pierre E. Jacob
80
14
0
21 Oct 2021
Quantification of empirical determinacy: the impact of likelihood
  weighting on posterior location and spread in Bayesian meta-analysis
  estimated with JAGS and INLA
Quantification of empirical determinacy: the impact of likelihood weighting on posterior location and spread in Bayesian meta-analysis estimated with JAGS and INLA
Sona Hunanyan
Håvard Rue
M. Plummer
M. Roos
82
2
0
24 Sep 2021
Gibbs posterior inference on a Levy density under discrete sampling
Gibbs posterior inference on a Levy density under discrete sampling
Zhe Wang
Ryan Martin
86
4
0
14 Sep 2021
Variational inference for cutting feedback in misspecified models
Variational inference for cutting feedback in misspecified models
Xue Yu
David J. Nott
M. Smith
73
14
0
25 Aug 2021
Mitigating Statistical Bias within Differentially Private Synthetic Data
Mitigating Statistical Bias within Differentially Private Synthetic Data
Sahra Ghalebikesabi
H. Wilde
Jack Jewson
Arnaud Doucet
Sandra Jeanne Vollmer
Chris Holmes
SyDa
85
7
0
24 Aug 2021
The Bayesian Learning Rule
The Bayesian Learning Rule
Mohammad Emtiyaz Khan
Håvard Rue
BDL
165
83
0
09 Jul 2021
Calibrating generalized predictive distributions
Calibrating generalized predictive distributions
Pei-Shien Wu
Ryan Martin
100
8
0
04 Jul 2021
Posterior Covariance Information Criterion for Weighted Inference
Posterior Covariance Information Criterion for Weighted Inference
Y. Iba
Keisuke Yano
59
3
0
25 Jun 2021
Approximate Bayesian Computation with Path Signatures
Approximate Bayesian Computation with Path Signatures
Joel Dyer
Patrick W Cannon
Sebastian M. Schmon
115
16
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
63
13
0
23 Jun 2021
Post-hoc loss-calibration for Bayesian neural networks
Post-hoc loss-calibration for Bayesian neural networks
Meet P. Vadera
S. Ghosh
Kenney Ng
Benjamin M. Marlin
UQCVBDL
88
7
0
13 Jun 2021
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
118
25
0
13 Jun 2021
Large Deviation Asymptotics and Bayesian Posterior Consistency on
  Stochastic Processes and Dynamical Systems
Large Deviation Asymptotics and Bayesian Posterior Consistency on Stochastic Processes and Dynamical Systems
Langxuan Su
Sayan Mukherjee
47
0
0
13 Jun 2021
An efficient adaptive MCMC algorithm for Pseudo-Bayesian quantum
  tomography
An efficient adaptive MCMC algorithm for Pseudo-Bayesian quantum tomography
The Tien Mai
41
1
0
01 Jun 2021
Bayesian inference under model misspecification using
  transport-Lagrangian distances: an application to seismic inversion
Bayesian inference under model misspecification using transport-Lagrangian distances: an application to seismic inversion
A. Scarinci
Michael Fehler
Youssef Marzouk
32
2
0
14 May 2021
Natural Posterior Network: Deep Bayesian Uncertainty for Exponential
  Family Distributions
Natural Posterior Network: Deep Bayesian Uncertainty for Exponential Family Distributions
Bertrand Charpentier
Oliver Borchert
Daniel Zügner
Simon Geisler
Stephan Günnemann
UQCVBDL
70
17
0
10 May 2021
PAC-Bayesian Matrix Completion with a Spectral Scaled Student Prior
PAC-Bayesian Matrix Completion with a Spectral Scaled Student Prior
The Tien Mai
60
2
0
16 Apr 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
Approximate Bayesian inference from noisy likelihoods with Gaussian
  process emulated MCMC
Approximate Bayesian inference from noisy likelihoods with Gaussian process emulated MCMC
Marko Jarvenpaa
J. Corander
61
5
0
08 Apr 2021
Synthetic Likelihood in Misspecified Models: Consequences and
  Corrections
Synthetic Likelihood in Misspecified Models: Consequences and Corrections
David T. Frazier
Christopher C. Drovandi
David J. Nott
73
10
0
08 Apr 2021
Post-Processing of MCMC
Post-Processing of MCMC
Leah F. South
M. Riabiz
Onur Teymur
Chris J. Oates
95
18
0
30 Mar 2021
Martingale posterior distributions
Martingale posterior distributions
Edwin Fong
Chris Holmes
S. Walker
UQCV
182
51
0
29 Mar 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
117
9
0
26 Mar 2021
Active multi-fidelity Bayesian online changepoint detection
Active multi-fidelity Bayesian online changepoint detection
Gregory W. Gundersen
Diana Cai
Chuteng Zhou
Barbara E. Engelhardt
Ryan P. Adams
56
10
0
26 Mar 2021
Posterior consistency for the spectral density of non-Gaussian
  stationary time series
Posterior consistency for the spectral density of non-Gaussian stationary time series
Yifu Tang
Claudia Kirch
J. Lee
R. Meyer
114
2
0
01 Mar 2021
Probabilistic Iterative Methods for Linear Systems
Probabilistic Iterative Methods for Linear Systems
Jon Cockayne
Ilse C. F. Ipsen
Chris J. Oates
T. W. Reid
113
11
0
23 Dec 2020
A comparison of learning rate selection methods in generalized Bayesian
  inference
A comparison of learning rate selection methods in generalized Bayesian inference
Pei-Shien Wu
Ryan Martin
BDL
76
48
0
21 Dec 2020
Bayes posterior convergence for loss functions via almost additive
  Thermodynamic Formalism
Bayes posterior convergence for loss functions via almost additive Thermodynamic Formalism
A. Lopes
Silvia R.C. Lopes
P. Varandas
66
7
0
10 Dec 2020
Gibbs posterior concentration rates under sub-exponential type losses
Gibbs posterior concentration rates under sub-exponential type losses
Nicholas Syring
Ryan Martin
124
29
0
08 Dec 2020
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
PAC$^m$-Bayes: Narrowing the Empirical Risk Gap in the Misspecified
  Bayesian Regime
PACm^mm-Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime
Warren Morningstar
Alexander A. Alemi
Joshua V. Dillon
130
16
0
19 Oct 2020
Minimax Quasi-Bayesian estimation in sparse canonical correlation
  analysis via a Rayleigh quotient function
Minimax Quasi-Bayesian estimation in sparse canonical correlation analysis via a Rayleigh quotient function
Qiuyun Zhu
Yves Atchadé
22
1
0
16 Oct 2020
Federated Generalized Bayesian Learning via Distributed Stein
  Variational Gradient Descent
Federated Generalized Bayesian Learning via Distributed Stein Variational Gradient Descent
Rahif Kassab
Osvaldo Simeone
FedML
93
46
0
11 Sep 2020
Tighter risk certificates for neural networks
Tighter risk certificates for neural networks
Maria Perez-Ortiz
Omar Rivasplata
John Shawe-Taylor
Csaba Szepesvári
UQCV
91
108
0
25 Jul 2020
An invitation to sequential Monte Carlo samplers
An invitation to sequential Monte Carlo samplers
Chenguang Dai
J. Heng
Pierre E. Jacob
N. Whiteley
134
68
0
23 Jul 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
qgam: Bayesian non-parametric quantile regression modelling in R
qgam: Bayesian non-parametric quantile regression modelling in R
Matteo Fasiolo
S. Wood
Margaux Zaffran
Raphael Nedellec
Y. Goude
33
60
0
07 Jul 2020
PAC-Bayes Analysis Beyond the Usual Bounds
PAC-Bayes Analysis Beyond the Usual Bounds
Omar Rivasplata
Ilja Kuzborskij
Csaba Szepesvári
John Shawe-Taylor
123
80
0
23 Jun 2020
Posterior Network: Uncertainty Estimation without OOD Samples via
  Density-Based Pseudo-Counts
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts
Bertrand Charpentier
Daniel Zügner
Stephan Günnemann
UQCVUDEDLBDL
119
186
0
16 Jun 2020
A generalized Bayes framework for probabilistic clustering
A generalized Bayes framework for probabilistic clustering
T. Rigon
A. Herring
David B. Dunson
66
27
0
09 Jun 2020
The role of exchangeability in causal inference
The role of exchangeability in causal inference
O. Saarela
D. Stephens
E. Moodie
126
7
0
02 Jun 2020
Information-Theoretic Generalization Bounds for Meta-Learning and
  Applications
Information-Theoretic Generalization Bounds for Meta-Learning and Applications
Sharu Theresa Jose
Osvaldo Simeone
87
47
0
09 May 2020
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