A comparison of learning rate selection methods in generalized Bayesian inference

21 December 2020

Papers citing "A comparison of learning rate selection methods in generalized Bayesian inference"

25 / 25 papers shown

Title
Predictive performance of power posteriors Yann McLatchie Edwin Fong David T. Frazier Jeremias Knoblauch 61 2 0 16 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
Weighted Particle-Based Optimization for Efficient Generalized Posterior Calibration Masahiro Tanaka 93 0 0 08 May 2024
Generalized Posterior Calibration via Sequential Monte Carlo Sampler Masahiro Tanaka 100 2 0 25 Apr 2024
Robust and Conjugate Gaussian Process Regression Matias Altamirano F. Briol Jeremias Knoblauch 84 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
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
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
Valid Inference for Machine Learning Model Parameters N. Dey Jonathan P. Williams 87 1 0 21 Feb 2023
Reliable Bayesian Inference in Misspecified Models David T. Frazier Robert Kohn Christopher C. Drovandi David Gunawan 80 5 0 13 Feb 2023
Robust and Scalable Bayesian Online Changepoint Detection Matias Altamirano F. Briol Jeremias Knoblauch 75 14 0 09 Feb 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
Sampling algorithms in statistical physics: a guide for statistics and machine learning Michael F Faulkner Samuel Livingstone 57 7 0 09 Aug 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 51 11 0 01 Apr 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
Gibbs posterior inference on a Levy density under discrete sampling Zhe Wang Ryan Martin 86 4 0 14 Sep 2021
Calibrating generalized predictive distributions Pei-Shien Wu Ryan Martin 100 8 0 04 Jul 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
Gibbs posterior concentration rates under sub-exponential type losses Nicholas Syring Ryan Martin 118 29 0 08 Dec 2020
Gibbs posterior inference on multivariate quantiles Indrabati Bhattacharya Ryan Martin 128 21 0 03 Feb 2020