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Memory-assisted reinforcement learning for diverse molecular de novo design
In de novo molecular design, recurrent neural networks (RNN) have been shown to be effective methods for sampling and generating novel chemical structures. Using a technique called reinforcement learning (RL), an RNN can be tuned to target a particular section of chemical space with optimized desira...
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| Publié dans: | J Cheminform |
|---|---|
| Auteurs principaux: | , , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
Springer International Publishing
2020
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7654024/ https://ncbi.nlm.nih.gov/pubmed/33292554 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s13321-020-00473-0 |
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