Improving the performance of models for one-step retrosynthesis through re-ranking

• Main Authors: Lin, Min Htoo, Tu, Zhengkai, Coley, Connor W.
• Other Authors: School of Physical and Mathematical Sciences
• Format: Article
• Language: English
• Published: 2022
• Subjects: Science::Chemistry; Computer-Aided Synthesis Planning; Energy-Based Model
• Online Access: https://hdl.handle.net/10356/163080
• Institution: Nanyang Technological University

Retrosynthesis is at the core of organic chemistry. Recently, the rapid growth of artificial intelligence (AI) has spurred a variety of novel machine learning approaches for data-driven synthesis planning. These methods learn complex patterns from reaction databases in order to predict, for a given...