v1v2 (latest)

A General Framework for Updating Belief Distributions

27 June 2013

Pier Giovanni Bissiri

Chris Holmes

S. Walker

ArXiv (abs)PDF HTML

Papers citing "A General Framework for Updating Belief Distributions"

50 / 204 papers shown

Title
The surrogate Gibbs-posterior of a corrected stochastic MALA: Towards uncertainty quantification for neural networks S. Bieringer Gregor Kasieczka Maximilian F. Steffen Mathias Trabs 89 1 0 13 Oct 2023
Hamiltonian Dynamics of Bayesian Inference Formalised by Arc Hamiltonian Systems Takuo Matsubara 33 0 0 11 Oct 2023
If there is no underfitting, there is no Cold Posterior Effect Yijie Zhang Yi-Shan Wu Luis A. Ortega A. Masegosa UQCV 66 1 0 02 Oct 2023
On the meaning of uncertainty for ethical AI: philosophy and practice Cassandra Bird Daniel Williamson Sabina Leonelli 37 1 0 11 Sep 2023
The Interpolating Information Criterion for Overparameterized Models Liam Hodgkinson Christopher van der Heide Roberto Salomone Fred Roosta Michael W. Mahoney 75 9 0 15 Jul 2023
Differentially Private Statistical Inference through $β$ -Divergence One Posterior Sampling Jack Jewson Sahra Ghalebikesabi Chris Holmes 82 2 0 11 Jul 2023
Some challenges of calibrating differentiable agent-based models Arnau Quera-Bofarull Joel Dyer Anisoara Calinescu Michael Wooldridge AI4CE 91 7 0 03 Jul 2023
G-TRACER: Expected Sharpness Optimization John R. Williams Stephen J. Roberts 52 0 0 24 Jun 2023
Semiparametric posterior corrections Andrew Yiu Edwin Fong Chris Holmes Judith Rousseau 228 4 0 09 Jun 2023
Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression You-Hyun Baek S. Berchuck Sayan Mukherjee 123 0 0 06 Jun 2023
On Consistent Bayesian Inference from Synthetic Data Ossi Raisa Hibiki Ito Antti Honkela SyDa 102 2 0 26 May 2023
Learning Robust Statistics for Simulation-based Inference under Model Misspecification Daolang Huang Ayush Bharti Amauri Souza Luigi Acerbi Samuel Kaski 118 35 0 25 May 2023
Bayesian calibration of differentiable agent-based models Arnau Quera-Bofarull Ayush Chopra Anisoara Calinescu Michael Wooldridge Joel Dyer 63 9 0 24 May 2023
Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation Richard Gao Michael Deistler Jakob H. Macke 133 13 0 24 May 2023
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods Veit Wild Sahra Ghalebikesabi Dino Sejdinovic Jeremias Knoblauch BDL UQCV 98 16 0 24 May 2023
Generalised likelihood profiles for models with intractable likelihoods D. Warne Oliver J. Maclaren E. Carr Matthew J. Simpson Christopher C. Drovandi 83 8 0 18 May 2023
Robustness of Bayesian ordinal response model against outliers via divergence approach Tomotaka Momozaki Tomoyuki Nakagawa 60 1 0 12 May 2023
Combining experimental and observational data through a power likelihood Xi Lin J. Tarp R. Evans CML 63 5 0 05 Apr 2023
Robustifying likelihoods by optimistically re-weighting data Miheer Dewaskar Christopher Tosh Jeremias Knoblauch David B. Dunson 91 6 0 19 Mar 2023
Kernel Density Bayesian Inverse Reinforcement Learning Aishwarya Mandyam Didong Li Jiayu Yao Diana Cai Andrew Jones Barbara E. Engelhardt OffRL BDL 90 3 0 13 Mar 2023
Bayes meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes Charles Riou Pierre Alquier Badr-Eddine Chérief-Abdellatif 117 10 0 23 Feb 2023
Reliable Bayesian Inference in Misspecified Models David T. Frazier Robert Kohn Christopher C. Drovandi David Gunawan 80 5 0 13 Feb 2023
Incorporating Expert Opinion on Observable Quantities into Statistical Models -- A General Framework P. Cooney Arthur J. White 28 1 0 10 Feb 2023
Robust and Scalable Bayesian Online Changepoint Detection Matias Altamirano F. Briol Jeremias Knoblauch 75 14 0 09 Feb 2023
Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference Ryan P. Kelly David J. Nott David T. Frazier D. Warne Christopher C. Drovandi 83 13 0 31 Jan 2023
$Semiparametric inference using fractional posteriors$ Semiparametric inference using fractional posteriors Alice L'Huillier Luke Travis I. Castillo Kolyan Ray 74 5 0 19 Jan 2023
The generalized IFS Bayesian method and an associated variational principle covering the classical and dynamical cases A. Lopes J. Mengue 29 2 0 02 Dec 2022
A General Framework for Cutting Feedback within Modularized Bayesian Inference Yang Liu Robert J. B. Goudie 67 8 0 07 Nov 2022
Leveraging variational autoencoders for multiple data imputation Breeshey Roskams-Hieter J. Wells S. Wade DRL 52 5 0 30 Sep 2022
How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences Mikolaj Kasprzak Ryan Giordano Tamara Broderick 70 4 0 29 Sep 2022
Solving Fredholm Integral Equations of the First Kind via Wasserstein Gradient Flows F. R. Crucinio Valentin De Bortoli Arnaud Doucet A. M. Johansen 61 3 0 16 Sep 2022
Investigating the Impact of Model Misspecification in Neural Simulation-based Inference Patrick W Cannon Daniel Ward Sebastian M. Schmon 78 36 0 05 Sep 2022
Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation Arnaud Delaunoy Joeri Hermans François Rozet Antoine Wehenkel Gilles Louppe 85 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
Bayesian non-conjugate regression via variational message passing C. Castiglione M. Bernardi 44 0 0 19 Jun 2022
Optimal quasi-Bayesian reduced rank regression with incomplete response The Tien Mai Pierre Alquier 102 2 0 17 Jun 2022
Generalised Bayesian Inference for Discrete Intractable Likelihood Takuo Matsubara Jeremias Knoblauch F. Briol Chris J. Oates 110 19 0 16 Jun 2022
Bayesian Learning of Parameterised Quantum Circuits Samuel Duffield Marcello Benedetti Matthias Rosenkranz 60 11 0 15 Jun 2022
Concentration of discrepancy-based approximate Bayesian computation via Rademacher complexity Sirio Legramanti Daniele Durante Pierre Alquier 92 6 0 14 Jun 2022
Bayesian Predictive Decision Synthesis Emily Tallman M. West 66 22 0 08 Jun 2022
Deep Bootstrap for Bayesian Inference Lizhen Nie Veronika Rockova UQCV BDL 180 3 0 30 May 2022
Bernstein - von Mises theorem and misspecified models: a review N. Bochkina 80 9 0 28 Apr 2022
Scalable Semi-Modular Inference with Variational Meta-Posteriors Chris U. Carmona Geoff K. Nicholls 53 11 0 01 Apr 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
Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation Viktor Bengs Eyke Hüllermeier Willem Waegeman EDL UQCV UD 90 43 0 11 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 88 45 0 09 Feb 2022
Variational Model Inversion Attacks Kuan-Chieh Wang Yanzhe Fu Ke Li Ashish Khisti R. Zemel Alireza Makhzani MIACV 94 98 0 26 Jan 2022
A generalized likelihood based Bayesian approach for scalable joint regression and covariance selection in high dimensions Srijata Samanta Kshitij Khare George Michailidis 132 8 0 14 Jan 2022