no code implementations • 7 Mar 2024 • Joonyoung F. Joung, Mun Hong Fong, Jihye Roh, Zhengkai Tu, John Bradshaw, Connor W. Coley
Mechanistic understanding of organic reactions can facilitate reaction development, impurity prediction, and in principle, reaction discovery.
1 code implementation • 8 Dec 2023 • Yujie Qian, Zhening Li, Zhengkai Tu, Connor W. Coley, Regina Barzilay
Conventionally, chemoinformatics models are trained with extensive structured data manually extracted from the literature.
1 code implementation • 19 May 2023 • Yujie Qian, Jiang Guo, Zhengkai Tu, Connor W. Coley, Regina Barzilay
Reaction diagram parsing is the task of extracting reaction schemes from a diagram in the chemistry literature.
1 code implementation • 30 Sep 2022 • Songtao Liu, Zhengkai Tu, Minkai Xu, Zuobai Zhang, Lu Lin, Rex Ying, Jian Tang, Peilin Zhao, Dinghao Wu
Current strategies use a decoupled approach of single-step retrosynthesis models and search algorithms, taking only the product as the input to predict the reactants for each planning step and ignoring valuable context information along the synthetic route.
1 code implementation • 28 May 2022 • Yujie Qian, Jiang Guo, Zhengkai Tu, Zhening Li, Connor W. Coley, Regina Barzilay
Molecular structure recognition is the task of translating a molecular image into its graph structure.
1 code implementation • 19 Oct 2021 • Zhengkai Tu, Connor W. Coley
Synthesis planning and reaction outcome prediction are two fundamental problems in computer-aided organic chemistry for which a variety of data-driven approaches have emerged.
Ranked #10 on Single-step retrosynthesis on USPTO-50k
no code implementations • EACL 2021 • Mohan Zhang, Luchen Tan, Zhengkai Tu, Zihang Fu, Kun Xiong, Ming Li, Jimmy Lin
The contribution of this work is a novel data generation technique using distant supervision that allows us to start with a pretrained sequence-to-sequence model and fine-tune a paraphrase generator that exhibits this behavior, allowing user-controllable paraphrase generation.
1 code implementation • 5 Feb 2020 • Ruixue Zhang, Wei Yang, Luyun Lin, Zhengkai Tu, Yuqing Xie, Zihang Fu, Yuhao Xie, Luchen Tan, Kun Xiong, Jimmy Lin
Techniques for automatically extracting important content elements from business documents such as contracts, statements, and filings have the potential to make business operations more efficient.