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

• Main Authors: Lin, Min Htoo, Tu, Zhengkai, Coley, Connor W.
• 其他作者: School of Physical and Mathematical Sciences
• 格式: Article
• 語言: English
• 出版: 2022
• 主題: Science::Chemistry; Computer-Aided Synthesis Planning; Energy-Based Model
• 在線閱讀: https://hdl.handle.net/10356/163080
• 機構: 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...