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

• المؤلفون الرئيسيون: Lin, Min Htoo, Tu, Zhengkai, Coley, Connor W.
• مؤلفون آخرون: School of Physical and Mathematical Sciences
• التنسيق: مقال
• اللغة: English
• منشور في: 2022
• الموضوعات: Science::Chemistry; Computer-Aided Synthesis Planning; Energy-Based Model
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/163080

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...