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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
Computing Bayes: Bayesian Computation from 1763 to the 21st Century
Computing Bayes: Bayesian Computation from 1763 to the 21st Century
G. Martin
David T. Frazier
Christian P. Robert
104
17
0
14 Apr 2020
Direct loss minimization algorithms for sparse Gaussian processes
Direct loss minimization algorithms for sparse Gaussian processes
Yadi Wei
Rishit Sheth
Roni Khardon
74
14
0
07 Apr 2020
Semi-Modular Inference: enhanced learning in multi-modular models by
  tempering the influence of components
Semi-Modular Inference: enhanced learning in multi-modular models by tempering the influence of components
Chris U. Carmona
Geoff K. Nicholls
122
27
0
15 Mar 2020
Training Binary Neural Networks using the Bayesian Learning Rule
Training Binary Neural Networks using the Bayesian Learning Rule
Xiangming Meng
Roman Bachmann
Mohammad Emtiyaz Khan
BDLMQ
103
43
0
25 Feb 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
Bayesian Deep Learning and a Probabilistic Perspective of Generalization
Bayesian Deep Learning and a Probabilistic Perspective of Generalization
A. Wilson
Pavel Izmailov
UQCVBDLOOD
175
658
0
20 Feb 2020
Observational nonidentifiability, generalized likelihood and free energy
Observational nonidentifiability, generalized likelihood and free energy
A. Allahverdyan
15
2
0
18 Feb 2020
Gibbs posterior inference on multivariate quantiles
Gibbs posterior inference on multivariate quantiles
Indrabati Bhattacharya
Ryan Martin
128
21
0
03 Feb 2020
Robust Inference and Model Criticism Using Bagged Posteriors
Robust Inference and Model Criticism Using Bagged Posteriors
Jonathan H. Huggins
Jeffrey W. Miller
142
15
0
15 Dec 2019
Diagnosing model misspecification and performing generalized Bayes'
  updates via probabilistic classifiers
Diagnosing model misspecification and performing generalized Bayes' updates via probabilistic classifiers
Owen Thomas
J. Corander
58
12
0
12 Dec 2019
Frequentist Consistency of Generalized Variational Inference
Frequentist Consistency of Generalized Variational Inference
Jeremias Knoblauch
66
11
0
10 Dec 2019
Equivariant online predictions of non-stationary time series
Equivariant online predictions of non-stationary time series
K. Takanashi
K. McAlinn
16
1
0
20 Nov 2019
Variational Predictive Information Bottleneck
Variational Predictive Information Bottleneck
Alexander A. Alemi
61
18
0
23 Oct 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
Correcting Predictions for Approximate Bayesian Inference
Correcting Predictions for Approximate Bayesian Inference
Tomasz Kuśmierczyk
J. Sakaya
Arto Klami
60
10
0
11 Sep 2019
Elements of asymptotic theory with outer probability measures
Elements of asymptotic theory with outer probability measures
J. Houssineau
Neil K. Chada
E. Delande
17
6
0
12 Aug 2019
Transport Monte Carlo: High-Accuracy Posterior Approximation via Random
  Transport
Transport Monte Carlo: High-Accuracy Posterior Approximation via Random Transport
L. Duan
OT
61
11
0
24 Jul 2019
Asymptotic normality, concentration, and coverage of generalized
  posteriors
Asymptotic normality, concentration, and coverage of generalized posteriors
Jeffrey W. Miller
89
68
0
22 Jul 2019
Adaptive particle-based approximations of the Gibbs posterior for
  inverse problems
Adaptive particle-based approximations of the Gibbs posterior for inverse problems
Z. Zou
S. Mukherjee
Harbir Antil
W. Aquino
51
6
0
02 Jul 2019
Adaptive Variable Selection for Sequential Prediction in Multivariate
  Dynamic Models
Adaptive Variable Selection for Sequential Prediction in Multivariate Dynamic Models
Isaac Lavine
Michael Lindon
M. West
AI4TS
75
22
0
15 Jun 2019
On the marginal likelihood and cross-validation
On the marginal likelihood and cross-validation
Edwin Fong
Chris Holmes
UQCV
138
111
0
21 May 2019
Robust Approximate Bayesian Inference with Synthetic Likelihood
Robust Approximate Bayesian Inference with Synthetic Likelihood
David T. Frazier
Christopher C. Drovandi
73
45
0
09 Apr 2019
Learning Attribute Patterns in High-Dimensional Structured Latent
  Attribute Models
Learning Attribute Patterns in High-Dimensional Structured Latent Attribute Models
Yuqi Gu
Gongjun Xu
46
24
0
08 Apr 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
Bayesian inference using synthetic likelihood: asymptotics and
  adjustments
Bayesian inference using synthetic likelihood: asymptotics and adjustments
David T. Frazier
David J. Nott
Christopher C. Drovandi
Robert Kohn
88
41
0
13 Feb 2019
Scalable Nonparametric Sampling from Multimodal Posteriors with the
  Posterior Bootstrap
Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap
Edwin Fong
Simon Lyddon
Chris Holmes
184
36
0
08 Feb 2019
Gibbs posterior convergence and the thermodynamic formalism
Gibbs posterior convergence and the thermodynamic formalism
K. Mcgoff
S. Mukherjee
A. Nobel
81
10
0
24 Jan 2019
A Modern Retrospective on Probabilistic Numerics
A Modern Retrospective on Probabilistic Numerics
Chris J. Oates
T. Sullivan
AI4CE
101
64
0
14 Jan 2019
Multilevel Monte Carlo Acceleration of Seismic Wave Propagation under
  Uncertainty
Multilevel Monte Carlo Acceleration of Seismic Wave Propagation under Uncertainty
M. Ballesio
Joakim Beck
Anamika Pandey
L. Parisi
E. von Schwerin
Raúl Tempone
11
12
0
03 Oct 2018
Nonparametric learning from Bayesian models with randomized objective
  functions
Nonparametric learning from Bayesian models with randomized objective functions
Simon Lyddon
S. Walker
C. C. Holmes
OOD
127
48
0
29 Jun 2018
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
78
58
0
06 Jun 2018
Principles of Bayesian Inference using General Divergence Criteria
Principles of Bayesian Inference using General Divergence Criteria
Jack Jewson
Jim Q. Smith
Chris Holmes
82
88
0
26 Feb 2018
Composite Gaussian Processes: Scalable Computation and Performance
  Analysis
Composite Gaussian Processes: Scalable Computation and Performance Analysis
Xiuming Liu
Dave Zachariah
Edith C.H. Ngai
23
0
0
31 Jan 2018
Robust Bayes-Like Estimation: Rho-Bayes estimation
Robust Bayes-Like Estimation: Rho-Bayes estimation
Y. Baraud
Lucien Birgé
72
4
0
22 Nov 2017
$α$-Variational Inference with Statistical Guarantees
ααα-Variational Inference with Statistical Guarantees
Yun Yang
D. Pati
A. Bhattacharya
61
25
0
09 Oct 2017
General Bayesian Updating and the Loss-Likelihood Bootstrap
General Bayesian Updating and the Loss-Likelihood Bootstrap
Simon Lyddon
Chris Holmes
S. Walker
142
122
0
22 Sep 2017
Fast calibrated additive quantile regression
Fast calibrated additive quantile regression
Matteo Fasiolo
S. Wood
Margaux Zaffran
Raphael Nedellec
Y. Goude
79
198
0
11 Jul 2017
Kinetic energy choice in Hamiltonian/hybrid Monte Carlo
Kinetic energy choice in Hamiltonian/hybrid Monte Carlo
Samuel Livingstone
Michael F Faulkner
Gareth O. Roberts
88
45
0
08 Jun 2017
Discontinuous Hamiltonian Monte Carlo for discrete parameters and
  discontinuous likelihoods
Discontinuous Hamiltonian Monte Carlo for discrete parameters and discontinuous likelihoods
Akihiko Nishimura
David B. Dunson
Jianfeng Lu
57
2
0
23 May 2017
Bayesian Probabilistic Numerical Methods
Bayesian Probabilistic Numerical Methods
Jon Cockayne
Chris J. Oates
T. Sullivan
Mark Girolami
122
166
0
13 Feb 2017
Bayesian fractional posteriors
Bayesian fractional posteriors
A. Bhattacharya
D. Pati
Yun Yang
121
110
0
03 Nov 2016
PAC-Bayesian Theory Meets Bayesian Inference
PAC-Bayesian Theory Meets Bayesian Inference
Pascal Germain
Francis R. Bach
Alexandre Lacoste
Simon Lacoste-Julien
121
184
0
27 May 2016
Communication-Efficient Distributed Statistical Inference
Communication-Efficient Distributed Statistical Inference
Michael I. Jordan
Jason D. Lee
Yun Yang
73
19
0
25 May 2016
Pseudo-Bayesian Quantum Tomography with Rank-adaptation
Pseudo-Bayesian Quantum Tomography with Rank-adaptation
The Tien Mai
Pierre Alquier
70
27
0
19 May 2016
Fast Rates for General Unbounded Loss Functions: from ERM to Generalized
  Bayes
Fast Rates for General Unbounded Loss Functions: from ERM to Generalized Bayes
Peter Grünwald
Nishant A. Mehta
227
73
0
01 May 2016
Data-driven priors and their posterior concentration rates
Data-driven priors and their posterior concentration rates
Ryan Martin
S. Walker
58
9
0
19 Apr 2016
Some comments about James Watson's and Chris Holmes' "Approximate Models
  and Robust Decisions": Nonparametric Bayesian clay for robust decision bricks
Some comments about James Watson's and Chris Holmes' "Approximate Models and Robust Decisions": Nonparametric Bayesian clay for robust decision bricks
Christian P. Robert
Judith Rousseau
AAML
52
1
0
30 Mar 2016
An Oracle Inequality for Quasi-Bayesian Non-Negative Matrix
  Factorization
An Oracle Inequality for Quasi-Bayesian Non-Negative Matrix Factorization
Pierre Alquier
Benjamin Guedj
140
17
0
06 Jan 2016
Probabilistic Integration: A Role in Statistical Computation?
Probabilistic Integration: A Role in Statistical Computation?
François‐Xavier Briol
Chris J. Oates
Mark Girolami
Michael A. Osborne
Dino Sejdinovic
161
53
0
03 Dec 2015
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