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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

11 December 2014
Peter Grünwald
T. V. Ommen
ArXivPDFHTML

Papers citing "Inconsistency of Bayesian Inference for Misspecified Linear Models, and a Proposal for Repairing It"

50 / 148 papers shown
Title
Learning Hyperparameters via a Data-Emphasized Variational Objective
Learning Hyperparameters via a Data-Emphasized Variational Objective
Ethan Harvey
Mikhail Petrov
Michael C. Hughes
65
0
0
03 Feb 2025
Learning the Regularization Strength for Deep Fine-Tuning via a Data-Emphasized Variational Objective
Learning the Regularization Strength for Deep Fine-Tuning via a Data-Emphasized Variational Objective
Ethan Harvey
Mikhail Petrov
Michael C. Hughes
45
0
0
28 Jan 2025
High-dimensional prediction for count response via sparse exponential
  weights
High-dimensional prediction for count response via sparse exponential weights
The Tien Mai
35
0
0
20 Oct 2024
Predictive variational inference: Learn the predictively optimal posterior distribution
Predictive variational inference: Learn the predictively optimal posterior distribution
Jinlin Lai
Yuling Yao
BDL
36
0
0
18 Oct 2024
Learning with Sparsely Permuted Data: A Robust Bayesian Approach
Learning with Sparsely Permuted Data: A Robust Bayesian Approach
Abhisek Chakraborty
Saptati Datta
35
0
0
16 Sep 2024
A sparse PAC-Bayesian approach for high-dimensional quantile prediction
A sparse PAC-Bayesian approach for high-dimensional quantile prediction
The Tien Mai
32
3
0
03 Sep 2024
Predictive performance of power posteriors
Predictive performance of power posteriors
Yann McLatchie
Edwin Fong
David T. Frazier
Jeremias Knoblauch
37
2
0
16 Aug 2024
Concentration of a sparse Bayesian model with Horseshoe prior in
  estimating high-dimensional precision matrix
Concentration of a sparse Bayesian model with Horseshoe prior in estimating high-dimensional precision matrix
The Tien Mai
46
2
0
20 Jun 2024
Detecting Model Misspecification in Amortized Bayesian Inference with
  Neural Networks: An Extended Investigation
Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks: An Extended Investigation
Marvin Schmitt
Paul-Christian Bürkner
Ullrich Kothe
Stefan T. Radev
48
7
0
05 Jun 2024
Adaptive posterior concentration rates for sparse high-dimensional
  linear regression with random design and unknown error variance
Adaptive posterior concentration rates for sparse high-dimensional linear regression with random design and unknown error variance
The Tien Mai
33
0
0
29 May 2024
Generalized Laplace Approximation
Generalized Laplace Approximation
Yinsong Chen
Samson S. Yu
Zhong Li
Chee Peng Lim
BDL
53
0
0
22 May 2024
Outlier-robust Kalman Filtering through Generalised Bayes
Outlier-robust Kalman Filtering through Generalised Bayes
Gerardo Duran-Martín
Matias Altamirano
Alexander Y. Shestopaloff
Leandro Sánchez-Betancourt
Jeremias Knoblauch
Matt Jones
F. Briol
Kevin P. Murphy
84
8
0
09 May 2024
Weighted Particle-Based Optimization for Efficient Generalized Posterior
  Calibration
Weighted Particle-Based Optimization for Efficient Generalized Posterior Calibration
Masahiro Tanaka
21
0
0
08 May 2024
On properties of fractional posterior in generalized reduced-rank
  regression
On properties of fractional posterior in generalized reduced-rank regression
The Tien Mai
36
1
0
27 Apr 2024
Variational Bayesian Last Layers
Variational Bayesian Last Layers
James Harrison
John Willes
Jasper Snoek
BDL
UQCV
63
25
0
17 Apr 2024
Concentration properties of fractional posterior in 1-bit matrix
  completion
Concentration properties of fractional posterior in 1-bit matrix completion
The Tien Mai
36
3
0
13 Apr 2024
On high-dimensional classification by sparse generalized Bayesian
  logistic regression
On high-dimensional classification by sparse generalized Bayesian logistic regression
The Tien Mai
46
1
0
19 Mar 2024
Bayesian Neural Networks with Domain Knowledge Priors
Bayesian Neural Networks with Domain Knowledge Priors
Dylan Sam
Rattana Pukdee
Daniel P. Jeong
Yewon Byun
J. Zico Kolter
BDL
UQCV
43
9
0
20 Feb 2024
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
Theodore Papamarkou
Maria Skoularidou
Konstantina Palla
Laurence Aitchison
Julyan Arbel
...
David Rügamer
Yee Whye Teh
Max Welling
Andrew Gordon Wilson
Ruqi Zhang
UQCV
BDL
55
27
0
01 Feb 2024
Inconsistency of cross-validation for structure learning in Gaussian
  graphical models
Inconsistency of cross-validation for structure learning in Gaussian graphical models
Zhao Lyu
Wai Ming Tai
Mladen Kolar
Bryon Aragam
CML
17
0
0
28 Dec 2023
Reproducible Parameter Inference Using Bagged Posteriors
Reproducible Parameter Inference Using Bagged Posteriors
Jonathan H. Huggins
Jeffrey W. Miller
UQCV
20
1
0
03 Nov 2023
A Risk Management Perspective on Statistical Estimation and Generalized
  Variational Inference
A Risk Management Perspective on Statistical Estimation and Generalized Variational Inference
Aurya Javeed
D. Kouri
T. Surowiec
22
2
0
26 Oct 2023
Sequential Gibbs Posteriors with Applications to Principal Component
  Analysis
Sequential Gibbs Posteriors with Applications to Principal Component Analysis
Steven Winter
Omar Melikechi
David B. Dunson
22
2
0
19 Oct 2023
On the Temperature of Bayesian Graph Neural Networks for Conformal
  Prediction
On the Temperature of Bayesian Graph Neural Networks for Conformal Prediction
Seohyeon Cha
Honggu Kang
Joonhyuk Kang
28
3
0
17 Oct 2023
On the Properties and Estimation of Pointwise Mutual Information
  Profiles
On the Properties and Estimation of Pointwise Mutual Information Profiles
Paweł Czyż
Frederic Grabowski
Julia E. Vogt
N. Beerenwinkel
Alexander Marx
27
2
0
16 Oct 2023
An Introduction to the Calibration of Computer Models
An Introduction to the Calibration of Computer Models
Richard D. Wilkinson
Christopher W. Lanyon
32
0
0
13 Oct 2023
Asymptotics for power posterior mean estimation
Asymptotics for power posterior mean estimation
Ruchira Ray
Marco Avella-Medina
Cynthia Rush
14
1
0
11 Oct 2023
If there is no underfitting, there is no Cold Posterior Effect
If there is no underfitting, there is no Cold Posterior Effect
Yijie Zhang
Yi-Shan Wu
Luis A. Ortega
A. Masegosa
UQCV
34
1
0
02 Oct 2023
A Unifying Perspective on Non-Stationary Kernels for Deeper Gaussian
  Processes
A Unifying Perspective on Non-Stationary Kernels for Deeper Gaussian Processes
M. Noack
Hengrui Luo
M. Risser
GP
32
11
0
18 Sep 2023
The fine print on tempered posteriors
The fine print on tempered posteriors
Konstantinos Pitas
Julyan Arbel
30
1
0
11 Sep 2023
FIND: A Function Description Benchmark for Evaluating Interpretability
  Methods
FIND: A Function Description Benchmark for Evaluating Interpretability Methods
Sarah Schwettmann
Tamar Rott Shaham
Joanna Materzyñska
Neil Chowdhury
Shuang Li
Jacob Andreas
David Bau
Antonio Torralba
18
20
0
07 Sep 2023
Information-theoretic Analysis of Test Data Sensitivity in Uncertainty
Information-theoretic Analysis of Test Data Sensitivity in Uncertainty
Futoshi Futami
Tomoharu Iwata
UD
PER
22
3
0
23 Jul 2023
A Novel Bayes' Theorem for Upper Probabilities
A Novel Bayes' Theorem for Upper Probabilities
Michele Caprio
Yusuf Sale
Eyke Hüllermeier
Insup Lee
28
10
0
13 Jul 2023
Multi-Predictor Fusion: Combining Learning-based and Rule-based
  Trajectory Predictors
Multi-Predictor Fusion: Combining Learning-based and Rule-based Trajectory Predictors
Sushant Veer
Apoorva Sharma
Marco Pavone
28
4
0
03 Jul 2023
Generalized Bayesian Inference for Scientific Simulators via Amortized
  Cost Estimation
Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation
Richard Gao
Michael Deistler
Jakob H. Macke
35
12
0
24 May 2023
Adversarial robustness of amortized Bayesian inference
Adversarial robustness of amortized Bayesian inference
Manuel Glöckler
Michael Deistler
Jakob H. Macke
AAML
29
14
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
17
1
0
12 May 2023
Exponential Stochastic Inequality
Exponential Stochastic Inequality
Peter Grünwald
M. F. Pérez-Ortiz
Zakaria Mhammedi
29
1
0
27 Apr 2023
Metrics for Bayesian Optimal Experiment Design under Model
  Misspecification
Metrics for Bayesian Optimal Experiment Design under Model Misspecification
Tommie A. Catanach
Niladri Das
16
4
0
17 Apr 2023
Combining experimental and observational data through a power likelihood
Combining experimental and observational data through a power likelihood
Xi Lin
J. Tarp
R. Evans
CML
21
5
0
05 Apr 2023
Robust probabilistic inference via a constrained transport metric
Robust probabilistic inference via a constrained transport metric
Abhisek Chakraborty
A. Bhattacharya
D. Pati
33
3
0
17 Mar 2023
Empirical Bayes inference in sparse high-dimensional generalized linear
  models
Empirical Bayes inference in sparse high-dimensional generalized linear models
Yiqi Tang
Ryan Martin
44
3
0
14 Mar 2023
Modern Bayesian Experimental Design
Modern Bayesian Experimental Design
Tom Rainforth
Adam Foster
Desi R. Ivanova
Freddie Bickford-Smith
37
78
0
28 Feb 2023
Valid Inference for Machine Learning Model Parameters
Valid Inference for Machine Learning Model Parameters
N. Dey
Jonathan P. Williams
19
1
0
21 Feb 2023
Semiparametric inference using fractional posteriors
Semiparametric inference using fractional posteriors
Alice L'Huillier
Luke Travis
I. Castillo
Kolyan Ray
17
5
0
19 Jan 2023
The E-Posterior
The E-Posterior
Peter D. Grünwald
UQCV
42
17
0
03 Jan 2023
A Survey of Learning Curves with Bad Behavior: or How More Data Need Not
  Lead to Better Performance
A Survey of Learning Curves with Bad Behavior: or How More Data Need Not Lead to Better Performance
Marco Loog
T. Viering
28
1
0
25 Nov 2022
Learning Causal Representations of Single Cells via Sparse Mechanism
  Shift Modeling
Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling
Romain Lopez
Natavsa Tagasovska
Stephen Ra
K. Cho
J. Pritchard
Aviv Regev
OOD
CML
DRL
36
35
0
07 Nov 2022
Meta-Uncertainty in Bayesian Model Comparison
Meta-Uncertainty in Bayesian Model Comparison
Marvin Schmitt
Stefan T. Radev
Paul-Christian Bürkner
UD
22
10
0
13 Oct 2022
Robust Neural Posterior Estimation and Statistical Model Criticism
Robust Neural Posterior Estimation and Statistical Model Criticism
Daniel Ward
Patrick W Cannon
Mark Beaumont
Matteo Fasiolo
Sebastian M. Schmon
37
38
0
12 Oct 2022
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