PGFS++: Molecular Property Improvement under Synthesis and Diversity Constraints
PGFS++ is introduced, a synthesis-aware reinforcement learning framework for input-specific molecular improvement that improves target properties while preserving high output diversity, and experiments show that PGFS++ improves target properties while preserving high output diversity.
Boqiao Zhang, Godbless James, S. Gottipati et al.
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