On Uncertainty Quantification for Near-Bayes Optimal Algorithms

On Uncertainty Quantification for Near-Bayes Optimal Algorithms

28 March 2024

Chris Holmes

Papers citing "On Uncertainty Quantification for Near-Bayes Optimal Algorithms"

6 / 6 papers shown

Title
Asymptotics for parametric martingale posteriors Edwin Fong Andrew Yiu 13 0 0 23 Oct 2024
Quasi-Bayes meets Vines David Huk Yuanhe Zhang Mark Steel Ritabrata Dutta 32 1 0 18 Jun 2024
Contraction rates for sparse variational approximations in Gaussian process regression D. Nieman Botond Szabó Harry Van Zanten 25 17 0 22 Sep 2021
AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data Nick Erickson Jonas W. Mueller Alexander Shirkov Hang Zhang Pedro Larroy Mu Li Alex Smola LMTD 84 598 0 13 Mar 2020
Why bigger is not always better: on finite and infinite neural networks Laurence Aitchison 173 51 0 17 Oct 2019
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,652 0 05 Dec 2016