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