Testing the limits of SMILES-based de novo molecular generation with curriculum and deep reinforcement learning
Deep reinforcement learning methods have been shown to be potentially powerful tools for de novo design. Recurrent-neural-network-based techniques are the most widely used methods in this space. In this work we examine the behaviour of recurrent-neural-network-based methods when there are few (or no...
| Autors principals: | , , , , , |
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| Format: | Journal article |
| Idioma: | English |
| Publicat: |
Springer Nature
2023
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