Enhanced thermophysical property prediction with uncertainty quantification using group contribution-Gaussian process regression

A hybrid method for reliable property prediction with uncertainty quantification that integrates group contribution with Gaussian process regression.

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Publication Details

Journal
Molecular Systems Design & Engineering
Published
2025-10-13
DOI
https://doi.org/10.1039/d5me00126a
Citations
1
Primary Topic
Gaussian Processes and Bayesian Inference
Type
article
Field-Weighted Citation Impact
2.48
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article

Enhanced thermophysical property prediction with uncertainty quantification using group contribution-Gaussian process regression

1 citations
Molecular Systems Design & Engineering
Gaussian Processes and Bayesian Inference
2.48
article

Enhanced thermophysical property prediction with uncertainty quantification using group contribution-Gaussian process regression

article en
1 citations

Abstract

A hybrid method for reliable property prediction with uncertainty quantification that integrates group contribution with Gaussian process regression.

Molecular Systems Design & EngineeringVol. 11(1)
University of Notre Dame (US), University of Aveiro (PT)
Climate action
Openalex Percentile: Top 6%
Gaussian Processes and Bayesian Inference
2.48
DOIOpen Access PDFOpenAlex
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Enhanced thermophysical property prediction with uncertainty quantification using group contribution-Gaussian process regression · Molecular Systems Design & Engineering (2025) | TGRS Research Map | TGRS