Evaluating Gaussian Process Metamodels and Sequential Designs for Noisy Level Set Estimation - Data

Name: Evaluating Gaussian Process Metamodels and Sequential Designs for Noisy Level Set Estimation - Data
Creator: University of California, Santa Barbara; Argonne National Laboratory
Published: 2021-03-03T00:00:00+08:00

Zenodo2021-03-03 更新2026-04-07 收录

水平集估计

高斯过程序贯设计

数据链接：

https://zenodo.org/record/4544145 数据链接链接失效反馈

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资源简介：

This is the simulation dataset for synthetic experiments (2D Modified Branin-Hoo function and 2D Michalewicz function) and case study (2D put option and 3D call option) in the article "Evaluating Gaussian Process Metamodels and Sequential Designs for Noisy Level Set Estimation". The code to generate the dataset is also uploaded to Zenodo (DOI 10.5281/zenodo.4579994).

提供机构：

University of California, Santa Barbara; Argonne National Laboratory

创建时间：

2021-03-03

Evaluating Gaussian Process Metamodels and Sequential Designs for Noisy Level Set Estimation - Data

资源简介：

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