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Constrained Bayesian optimization for automatic chemical design using variational autoencoders
Automatic Chemical Design is a framework for generating novel molecules with optimized properties. The original scheme, featuring Bayesian optimization over the latent space of a variational autoencoder, suffers from the pathology that it tends to produce invalid molecular structures. First, we demo...
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| Pubblicato in: | Chem Sci |
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| Autori principali: | , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Royal Society of Chemistry
2019
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7067240/ https://ncbi.nlm.nih.gov/pubmed/32190274 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1039/c9sc04026a |
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