v1v2v3 (latest)

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

11 December 2014

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

50 / 148 papers shown

Title
Robust Neural Posterior Estimation and Statistical Model Criticism Daniel Ward Patrick W Cannon Mark Beaumont Matteo Fasiolo Sebastian M. Schmon 90 39 0 12 Oct 2022
Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation Arnaud Delaunoy Joeri Hermans François Rozet Antoine Wehenkel Gilles Louppe 83 34 0 29 Aug 2022
Sampling algorithms in statistical physics: a guide for statistics and machine learning Michael F Faulkner Samuel Livingstone 57 7 0 09 Aug 2022
Tuning Stochastic Gradient Algorithms for Statistical Inference via Large-Sample Asymptotics Jeffrey Negrea Jun Yang Haoyue Feng Daniel M. Roy Jonathan H. Huggins 63 1 0 25 Jul 2022
The Importance Markov Chain Charly Andral Randal Douc Hugo Marival Christian P. Robert 76 5 0 17 Jul 2022
Variational Inference of overparameterized Bayesian Neural Networks: a theoretical and empirical study Tom Huix Szymon Majewski Alain Durmus Eric Moulines Anna Korba BDL 52 6 0 08 Jul 2022
Cold Posteriors through PAC-Bayes Konstantinos Pitas Julyan Arbel 89 5 0 22 Jun 2022
Optimal quasi-Bayesian reduced rank regression with incomplete response The Tien Mai Pierre Alquier 102 2 0 17 Jun 2022
Deep Bootstrap for Bayesian Inference Lizhen Nie Veronika Rockova UQCV BDL 179 3 0 30 May 2022
How Tempering Fixes Data Augmentation in Bayesian Neural Networks Gregor Bachmann Lorenzo Noci Thomas Hofmann BDL AAML 125 9 0 27 May 2022
Bernstein - von Mises theorem and misspecified models: a review N. Bochkina 74 9 0 28 Apr 2022
Scalable Semi-Modular Inference with Variational Meta-Posteriors Chris U. Carmona Geoff K. Nicholls 51 11 0 01 Apr 2022
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification Sanyam Kapoor Wesley J. Maddox Pavel Izmailov A. Wilson BDL UD 94 51 0 30 Mar 2022
Modularized Bayesian analyses and cutting feedback in likelihood-free inference Atlanta Chakraborty David J. Nott Christopher C. Drovandi David T. Frazier Scott A. Sisson 72 14 0 18 Mar 2022
Robust PAC $^m$ : Training Ensemble Models Under Misspecification and Outliers Matteo Zecchin Sangwoo Park Osvaldo Simeone Marios Kountouris David Gesbert 89 5 0 03 Mar 2022
Cutting feedback and modularized analyses in generalized Bayesian inference David T. Frazier David J. Nott 92 7 0 21 Feb 2022
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap Charita Dellaporta Jeremias Knoblauch Theodoros Damoulas F. Briol 82 45 0 09 Feb 2022
The no-free-lunch theorems of supervised learning T. Sterkenburg Peter Grünwald FedML 78 59 0 09 Feb 2022
Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks Marvin Schmitt Paul-Christian Bürkner Ullrich Kothe Stefan T. Radev 104 39 0 16 Dec 2021
Uncertainty estimation under model misspecification in neural network regression Maria R. Cervera Rafael Dätwyler Francesco DÁngelo Hamza Keurti Benjamin Grewe Christian Henning 64 6 0 23 Nov 2021
Posterior concentration and fast convergence rates for generalized Bayesian learning L. Ho Binh T. Nguyen Vu C. Dinh D. M. Nguyen 58 5 0 19 Nov 2021
User-friendly introduction to PAC-Bayes bounds Pierre Alquier FedML 193 206 0 21 Oct 2021
Asymptotics of cut distributions and robust modular inference using Posterior Bootstrap E. Pompe Pierre E. Jacob 80 14 0 21 Oct 2021
Gibbs posterior inference on a Levy density under discrete sampling Zhe Wang Ryan Martin 80 4 0 14 Sep 2021
Laplace and Saddlepoint Approximations in High Dimensions Yanbo Tang Nancy Reid 63 7 0 22 Jul 2021
Calibrating generalized predictive distributions Pei-Shien Wu Ryan Martin 100 8 0 04 Jul 2021
Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect Lorenzo Noci Kevin Roth Gregor Bachmann Sebastian Nowozin Thomas Hofmann CML 84 26 0 11 Jun 2021
Data augmentation in Bayesian neural networks and the cold posterior effect Seth Nabarro Stoil Ganev Adrià Garriga-Alonso Vincent Fortuin Mark van der Wilk Laurence Aitchison BDL 92 41 0 10 Jun 2021
An efficient adaptive MCMC algorithm for Pseudo-Bayesian quantum tomography The Tien Mai 34 1 0 01 Jun 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 137 134 0 14 May 2021
On the Robustness to Misspecification of $α$ -Posteriors and Their Variational Approximations Marco Avella-Medina J. M. Olea Cynthia Rush Amilcar Velez 75 19 0 16 Apr 2021
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 Takuo Matsubara Jeremias Knoblauch François‐Xavier Briol Chris J. Oates UQCV 80 80 0 15 Apr 2021
Synthetic Likelihood in Misspecified Models: Consequences and Corrections David T. Frazier Christopher C. Drovandi David J. Nott 73 10 0 08 Apr 2021
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 Gregory W. Gundersen Diana Cai Chuteng Zhou Barbara E. Engelhardt Ryan P. Adams 56 10 0 26 Mar 2021
The Shape of Learning Curves: a Review T. Viering Marco Loog 80 135 0 19 Mar 2021
Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation Mayee F. Chen Benjamin Cohen-Wang Stephen Mussmann Frederic Sala Christopher Ré 91 10 0 03 Mar 2021
DEUP: Direct Epistemic Uncertainty Prediction Salem Lahlou Moksh Jain Hadi Nekoei V. Butoi Paul Bertin Jarrid Rector-Brooks Maksym Korablyov Yoshua Bengio PER UQLM UQCV UD 317 94 0 16 Feb 2021
A comparison of learning rate selection methods in generalized Bayesian inference Pei-Shien Wu Ryan Martin BDL 68 48 0 21 Dec 2020
Gibbs posterior concentration rates under sub-exponential type losses Nicholas Syring Ryan Martin 115 29 0 08 Dec 2020
Robustness on Networks Marios Papamichalis Simón Lunagómez P. Wolfe 25 0 0 05 Dec 2020
Foundations of Bayesian Learning from Synthetic Data H. Wilde Jack Jewson Sebastian J. Vollmer Chris Holmes 87 15 0 16 Nov 2020
Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty Estimation Aurick Zhou Sergey Levine BDL OOD UQCV 48 13 0 05 Nov 2020
PAC $^m$ -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
Probabilistic Machine Learning for Healthcare Irene Y. Chen Shalmali Joshi Marzyeh Ghassemi Rajesh Ranganath OOD 74 56 0 23 Sep 2020
A statistical theory of cold posteriors in deep neural networks Laurence Aitchison UQCV BDL 90 70 0 13 Aug 2020
An invitation to sequential Monte Carlo samplers Chenguang Dai J. Heng Pierre E. Jacob N. Whiteley 134 68 0 23 Jul 2020
Optimal Bayesian estimation of Gaussian mixtures with growing number of components Ilsang Ohn Lizhen Lin 67 18 0 17 Jul 2020
Finite mixture models do not reliably learn the number of components Diana Cai Trevor Campbell Tamara Broderick 66 23 0 08 Jul 2020