Augmenting Stationary Covariance Functions with a Smoothness Hyperparameter and Improving Gaussian Process Regression Using a Structural Similarity Index
{"title":"Augmenting Stationary Covariance Functions with a Smoothness Hyperparameter and Improving Gaussian Process Regression Using a Structural Similarity Index","authors":"A. Chlingaryan, Raymond Leung, A. Melkumyan","doi":"10.1007/s11004-023-10095-5","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":51117,"journal":{"name":"Mathematical Geosciences","volume":"594 1","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Geosciences","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1007/s11004-023-10095-5","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
期刊介绍:
Mathematical Geosciences (formerly Mathematical Geology) publishes original, high-quality, interdisciplinary papers in geomathematics focusing on quantitative methods and studies of the Earth, its natural resources and the environment. This international publication is the official journal of the IAMG. Mathematical Geosciences is an essential reference for researchers and practitioners of geomathematics who develop and apply quantitative models to earth science and geo-engineering problems.