Replication or exploration? Sequential design for stochastic simulation experiments

9 October 2017

Papers citing "Replication or exploration? Sequential design for stochastic simulation experiments"

8 / 8 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
Future Aware Safe Active Learning of Time Varying Systems using Gaussian Processes Markus Lange-Hegermann Christoph Zimmer AI4TS 42 0 0 17 May 2024
Active Learning of Piecewise Gaussian Process Surrogates Chiwoo Park R. Waelder Bonggwon Kang Benji Maruyama Soondo Hong R. Gramacy GP 16 1 0 20 Jan 2023
Multi-objective hyperparameter optimization with performance uncertainty A. Hernández I. Nieuwenhuyse Gonzalo Nápoles 14 2 0 09 Sep 2022
Bayesian multi-objective optimization for stochastic simulators: an extension of the Pareto Active Learning method Bruno Barracosa Julien Bect H. Baraffe J. Morin Josselin Fournel E. Vázquez 17 2 0 08 Jul 2022
A survey on multi-objective hyperparameter optimization algorithms for Machine Learning A. Hernández I. Nieuwenhuyse Sebastian Rojas Gonzalez 19 95 0 23 Nov 2021
Kernels over Sets of Finite Sets using RKHS Embeddings, with Application to Bayesian (Combinatorial) Optimization Poompol Buathong D. Ginsbourger Tipaluck Krityakierne BDL 24 22 0 09 Oct 2019
Mercer kernels and integrated variance experimental design: connections between Gaussian process regression and polynomial approximation Alex A. Gorodetsky Youssef M. Marzouk 34 38 0 27 Feb 2015