Compressed graph representation for scalable molecular graph generation
Abstract Recently, deep learning has been successfully applied to molecular graph generation.Nevertheless, mitigating the computational complexity, cga 200 to cga 510 adapter which increases with the number of nodes in a graph, has been a major challenge.This has hindered the application of deep learning-based molecular graph generation to large mo