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Nonparametric learning from Bayesian models with randomized objective functions

29 June 2018

C. C. Holmes

Papers citing "Nonparametric learning from Bayesian models with randomized objective functions"

24 / 24 papers shown

Title
Decision Making under Model Misspecification: DRO with Robust Bayesian Ambiguity Sets Charita Dellaporta Patrick O'Hara Theodoros Damoulas 115 0 0 06 May 2025
A Deep Bayesian Nonparametric Framework for Robust Mutual Information Estimation Forough Fazeliasl Michael Minyi Zhang Bei Jiang Linglong Kong 83 0 0 13 Mar 2025
Predictive Coresets Bernardo Flores 100 0 0 08 Feb 2025
Generative vs. Discriminative modeling under the lens of uncertainty quantification Elouan Argouarc'h François Desbouvries Eric Barat Eiji Kawasaki UQCV 68 0 0 13 Jun 2024
Posterior Uncertainty Quantification in Neural Networks using Data Augmentation Luhuan Wu Sinead Williamson UQCV 89 7 0 18 Mar 2024
Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling Hyungi Lee G. Nam Edwin Fong Juho Lee BDL 75 6 0 12 Mar 2024
Bayesian Nonparametrics Meets Data-Driven Distributionally Robust Optimization Nicola Bariletto Nhat Ho OOD 111 1 0 28 Jan 2024
Reproducible Parameter Inference Using Bagged Posteriors Jonathan H. Huggins Jeffrey W. Miller UQCV 121 1 0 03 Nov 2023
On the Properties and Estimation of Pointwise Mutual Information Profiles Paweł Czyż Frederic Grabowski Julia E. Vogt N. Beerenwinkel Alexander Marx 83 3 0 16 Oct 2023
Robustness of Bayesian ordinal response model against outliers via divergence approach Tomotaka Momozaki Tomoyuki Nakagawa 54 1 0 12 May 2023
Robustifying likelihoods by optimistically re-weighting data Miheer Dewaskar Christopher Tosh Jeremias Knoblauch David B. Dunson 89 6 0 19 Mar 2023
A Semi-Bayesian Nonparametric Estimator of the Maximum Mean Discrepancy Measure: Applications in Goodness-of-Fit Testing and Generative Adversarial Networks Forough Fazeli Asl M. Zhang Lizhen Lin 77 1 0 05 Mar 2023
Bayesian Quantification with Black-Box Estimators Albert Ziegler Paweł Czyż UQCV 52 0 0 17 Feb 2023
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
Asymptotics of cut distributions and robust modular inference using Posterior Bootstrap E. Pompe Pierre E. Jacob 80 14 0 21 Oct 2021
Nonparametric posterior learning for emission tomography with multimodal data F. Goncharov Éric Barat T. Dautremer MedIm 53 0 0 29 Jul 2021
Martingale posterior distributions Edwin Fong Chris Holmes S. Walker UQCV 180 51 0 29 Mar 2021
Introducing prior information in Weighted Likelihood Bootstrap with applications to model misspecification E. Pompe 117 9 0 26 Mar 2021
Bayesian Bootstrap Spike-and-Slab LASSO Lizhen Nie Veronika Rockova 184 32 0 29 Nov 2020
Robust Bayesian Inference for Discrete Outcomes with the Total Variation Distance Jeremias Knoblauch Lara Vomfell 72 7 0 26 Oct 2020
A general Bayesian bootstrap for censored data based on the beta-Stacy process Andrea Arfe P. Muliere 125 2 0 10 Feb 2020
Robust Inference and Model Criticism Using Bagged Posteriors Jonathan H. Huggins Jeffrey W. Miller 142 15 0 15 Dec 2019
Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap Edwin Fong Simon Lyddon Chris Holmes 184 36 0 08 Feb 2019
Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness Sebastian J. Vollmer Bilal A. Mateen G. Bohner Franz J. Király Rayid Ghani ... Karel G. M. Moons Gary S. Collins J. Ioannidis Chris Holmes H. Hemingway 124 39 0 21 Dec 2018