May 8, 2024, 4:43 a.m. | Hyunseung Kim (Seoul National University), Haeyeon Choi (Ewha Womans University), Dongju Kang (Seoul National University), Won Bo Lee (Seoul National

cs.LG updates on

arXiv:2303.11833v2 Announce Type: replace-cross
Abstract: The goal of most materials discovery is to discover materials that are superior to those currently known. Fundamentally, this is close to extrapolation, which is a weak point for most machine learning models that learn the probability distribution of data. Herein, we develop reinforcement learning-guided combinatorial chemistry, which is a rule-based molecular designer driven by trained policy for selecting subsequent molecular fragments to get a target molecule. Since our model has the potential to generate …

abstract arxiv chemistry cs.lg data discovery distribution learn machine machine learning machine learning models materials probability reinforcement reinforcement learning type via

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