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Autonomous design of new chemical reactions using a variational autoencoder
Artificial intelligence based chemistry models are a promising method of exploring chemical reaction design spaces. However, training datasets based on experimental synthesis are typically reported only for the optimal synthesis reactions. This leads to an inherited bias in the model predictions. Th...
Autores principales: | Tempke, Robert, Musho, Terence |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814385/ https://www.ncbi.nlm.nih.gov/pubmed/36697652 http://dx.doi.org/10.1038/s42004-022-00647-x |
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