Practical heteroskedastic Gaussian process modeling for large simulation experiments

17 November 2016

Papers citing "Practical heteroskedastic Gaussian process modeling for large simulation experiments"

7 / 7 papers shown

Title
Adaptive Replication Strategies in Trust-Region-Based Bayesian Optimization of Stochastic Functions Mickael Binois Jeffrey Larson 71 0 0 29 Apr 2025
Multi-Response Heteroscedastic Gaussian Process Models and Their Inference Taehee Lee Jun S. Liu 6 1 0 29 Aug 2023
A review of predictive uncertainty estimation with machine learning Hristos Tyralis Georgia Papacharalampous UD UQCV 43 42 0 17 Sep 2022
Stochastic polynomial chaos expansions to emulate stochastic simulators X. Zhu Bruno Sudret 11 17 0 07 Feb 2022
mlOSP: Towards a Unified Implementation of Regression Monte Carlo Algorithms M. Ludkovski 18 7 0 01 Dec 2020
Energy consumption forecasting using a stacked nonparametric Bayesian approach Dilusha Weeraddana N. Khoa Lachlan OÑeil Weihong Wang C. Cai AI4TS 6 3 0 11 Nov 2020
Local Gaussian process approximation for large computer experiments R. Gramacy D. Apley 98 391 0 02 Mar 2013