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Evaluation of Reinforcement Learning in Transformer-based Molecular Design

By Jiazhen He and others
Designing compounds with a range of desirable properties is a fundamental challenge in drug discovery. In pre-clinical early drug discovery, novel compounds are often designed based on an already existing promising starting compound through structural modifications for further property optimization. Recently, transformer-based deep learning models have been explored for the task of molecular... Show more
July 10, 2024
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Evaluation of Reinforcement Learning in Transformer-based Molecular Design
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