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A General Framework for Updating Belief Distributions

27 June 2013

Pier Giovanni Bissiri

Chris Holmes

S. Walker

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Papers citing "A General Framework for Updating Belief Distributions"

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Title
Addressing the Inconsistency in Bayesian Deep Learning via Generalized Laplace Approximation Yinsong Chen Samson S. Yu Zhong Li Chee Peng Lim BDL 78 0 0 01 Jul 2025
Variational Deep Learning via Implicit Regularization Jonathan Wenger Beau Coker Juraj Marusic John P. Cunningham OOD UQCV BDL 56 0 0 26 May 2025
High-dimensional Bayesian Tobit regression for censored response with Horseshoe prior Tien Mai 61 2 0 13 May 2025
Decision Making under Model Misspecification: DRO with Robust Bayesian Ambiguity Sets Charita Dellaporta Patrick O'Hara Theodoros Damoulas 119 0 0 06 May 2025
Structural Inference: Interpreting Small Language Models with Susceptibilities Garrett Baker George Wang Jesse Hoogland Daniel Murfet AAML 157 1 0 25 Apr 2025
A Weighted-likelihood framework for class imbalance in Bayesian prediction models Stanley E. Lazic 82 0 0 23 Apr 2025
Correcting Mode Proportion Bias in Generalized Bayesian Inference via a Weighted Kernel Stein Discrepancy Elham Afzali Saman Muthukumarana Liqun Wang 87 0 0 03 Mar 2025
AI-Powered Bayesian Inference Veronika Rockova Sean O'Hagan 463 0 0 26 Feb 2025
Misspecification-robust likelihood-free inference in high dimensions Owen Thomas Raquel Sá-Leao H. Lencastre Samuel Kaski J. Corander Henri Pesonen 242 9 0 17 Feb 2025
Test-Time Alignment via Hypothesis Reweighting Yoonho Lee Jonathan Williams Henrik Marklund Archit Sharma E. Mitchell Anikait Singh Chelsea Finn 141 5 0 11 Dec 2024
Expert-elicitation method for non-parametric joint priors using normalizing flows F. Bockting Stefan T. Radev Paul-Christian Bürkner BDL 209 2 0 24 Nov 2024
Streaming Bayes GFlowNets Tiago da Silva Daniel Augusto R. M. A. de Souza Diego Mesquita BDL 158 2 0 08 Nov 2024
MAP: Multi-Human-Value Alignment Palette Xinran Wang Qi Le A. N. Ahmed Enmao Diao Yi Zhou Nathalie Baracaldo Jie Ding Ali Anwar 56 5 0 24 Oct 2024
Asymptotics for parametric martingale posteriors Edwin Fong Andrew Yiu 54 0 0 23 Oct 2024
High-dimensional prediction for count response via sparse exponential weights The Tien Mai 71 0 0 20 Oct 2024
Predictive variational inference: Learn the predictively optimal posterior distribution Jinlin Lai Yuling Yao BDL 94 0 0 18 Oct 2024
Spectral Representations for Accurate Causal Uncertainty Quantification with Gaussian Processes Hugh Dance Peter Orbanz Arthur Gretton CML 61 1 0 18 Oct 2024
Generating Origin-Destination Matrices in Neural Spatial Interaction Models Ioannis Zachos Mark Girolami Theodoros Damoulas 58 1 0 09 Oct 2024
Temperature Optimization for Bayesian Deep Learning Kenyon Ng Chris van der Heide Liam Hodgkinson Susan Wei BDL 124 0 0 08 Oct 2024
Differentiation and Specialization of Attention Heads via the Refined Local Learning Coefficient George Wang Jesse Hoogland Stan van Wingerden Zach Furman Daniel Murfet OffRL 86 9 0 03 Oct 2024
A sparse PAC-Bayesian approach for high-dimensional quantile prediction The Tien Mai 74 3 0 03 Sep 2024
Dataset Distillation from First Principles: Integrating Core Information Extraction and Purposeful Learning Vyacheslav Kungurtsev Yuanfang Peng Jianyang Gu Saeed Vahidian Anthony Quinn Fadwa Idlahcen Yiran Chen FedML DD 116 2 0 02 Sep 2024
Scalable Bayesian Clustering for Integrative Analysis of Multi-View Data Rafael Cabral Maria de Iorio Andrew Harris 36 0 0 30 Aug 2024
Loss-based Bayesian Sequential Prediction of Value at Risk with a Long-Memory and Non-linear Realized Volatility Model Rangika Peiris Minh-Ngoc Tran Chao Wang Richard Gerlach 25 0 0 24 Aug 2024
Predictive performance of power posteriors Yann McLatchie Edwin Fong David T. Frazier Jeremias Knoblauch 61 2 0 16 Aug 2024
Randomized Transport Plans via Hierarchical Fully Probabilistic Design Sarah Boufelja Anthony Quinn Robert Shorten OT 120 0 0 04 Aug 2024
Concentration of a sparse Bayesian model with Horseshoe prior in estimating high-dimensional precision matrix The Tien Mai 67 4 0 20 Jun 2024
Approximation-Aware Bayesian Optimization Natalie Maus Kyurae Kim Geoff Pleiss David Eriksson John P. Cunningham Jacob R. Gardner 67 3 0 06 Jun 2024
Adaptive posterior concentration rates for sparse high-dimensional linear regression with random design and unknown error variance The Tien Mai 66 0 0 29 May 2024
Generalised Bayes Linear Inference L. Astfalck Cassandra Bird Daniel Williamson AI4CE 62 0 0 23 May 2024
Addressing Misspecification in Simulation-based Inference through Data-driven Calibration Antoine Wehenkel Juan L. Gamella Ozan Sener Jens Behrmann Guillermo Sapiro Marco Cuturi J. Jacobsen UQLM 143 11 0 14 May 2024
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 138 11 0 09 May 2024
Weighted Particle-Based Optimization for Efficient Generalized Posterior Calibration Masahiro Tanaka 93 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 88 2 0 27 Apr 2024
Generalized Posterior Calibration via Sequential Monte Carlo Sampler Masahiro Tanaka 100 2 0 25 Apr 2024
On Neighbourhood Cross Validation Simon N. Wood 23 1 0 25 Apr 2024
Distributed Fractional Bayesian Learning for Adaptive Optimization Yaqun Yang Jinlong Lei Guanghui Wen Yiguang Hong 133 0 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 58 5 0 13 Apr 2024
On high-dimensional classification by sparse generalized Bayesian logistic regression The Tien Mai 73 2 0 19 Mar 2024
Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods? Mira Jürgens Nis Meinert Viktor Bengs Eyke Hüllermeier Willem Waegeman UQCV UD PER EDL BDL 111 15 0 14 Feb 2024
Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation Julius Vetter Guy Moss Cornelius Schroder Richard Gao Jakob H. Macke 94 5 0 12 Feb 2024
Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage? Maohao Shen J. Jon Ryu Soumya Ghosh Yuheng Bu P. Sattigeri Subhro Das Greg Wornell EDL BDL UQCV 74 3 0 09 Feb 2024
Bootstrap Your Own Variance Polina Turishcheva Jason Ramapuram Sinead Williamson Dan Busbridge Eeshan Gunesh Dhekane Russ Webb UQCV 66 0 0 06 Dec 2023
A General Space of Belief Updates for Model Misspecification in Bayesian Networks Tianjin Li 59 0 0 09 Nov 2023
Reproducible Parameter Inference Using Bagged Posteriors Jonathan H. Huggins Jeffrey W. Miller UQCV 128 1 0 03 Nov 2023
ABC-based Forecasting in State Space Models Chaya Weerasinghe Rubén Loaiza-Maya G. Martin David T. Frazier 47 1 0 02 Nov 2023
Robust and Conjugate Gaussian Process Regression Matias Altamirano F. Briol Jeremias Knoblauch 87 13 0 01 Nov 2023
A Risk Management Perspective on Statistical Estimation and Generalized Variational Inference Aurya Javeed D. Kouri T. Surowiec 80 2 0 26 Oct 2023
Sequential Gibbs Posteriors with Applications to Principal Component Analysis Steven Winter Omar Melikechi David B. Dunson 74 2 0 19 Oct 2023
An Introduction to the Calibration of Computer Models Richard D. Wilkinson Christopher W. Lanyon 52 0 0 13 Oct 2023