Bayesian chemical reaction neural network for autonomous kinetic uncertainty quantification

Bayesian chemical reaction neural network for autonomous kinetic uncertainty quantification

<jats:p>We develop Bayesian Chemical Reaction Neural Network (B-CRNN), a method to infer chemical reaction models and provide the associated uncertainty purely from data without prior knowledge of reaction templates.</jats:p>

Bibliographic Details
Main Authors: Li, Qiaofeng, Chen, Huaibo, Koenig, Benjamin C, Deng, Sili
Other Authors: Massachusetts Institute of Technology. Department of Mechanical Engineering
Format: Article
Language:English
Published: Royal Society of Chemistry (RSC) 2023
Online Access:https://hdl.handle.net/1721.1/148449

Internet

https://hdl.handle.net/1721.1/148449

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