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>
| Auteurs principaux: | , , , |
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| Autres auteurs: | |
| Format: | Article |
| Langue: | English |
| Publié: |
Royal Society of Chemistry (RSC)
2023
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| Accès en ligne: | https://hdl.handle.net/1721.1/148449 |
| Résumé: | <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> |
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