Search Results for author:
Found 8 papers, 6 papers with code
Beyond Major Product Prediction: Reproducing Reaction Mechanisms with Machine Learning Models Trained on a Large-Scale Mechanistic Dataset
Mechanistic understanding of organic reactions can facilitate reaction development, impurity prediction, and in principle, reaction discovery.
Predictive Chemistry Augmented with Text Retrieval
Conventionally, chemoinformatics models are trained with extensive structured data manually extracted from the literature.
RxnScribe: A Sequence Generation Model for Reaction Diagram Parsing
Reaction diagram parsing is the task of extracting reaction schemes from a diagram in the chemistry literature.
FusionRetro: Molecule Representation Fusion via In-Context Learning for Retrosynthetic Planning
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.
MolScribe: Robust Molecular Structure Recognition with Image-To-Graph Generation
Molecular structure recognition is the task of translating a molecular image into its graph structure.
Permutation invariant graph-to-sequence model for template-free retrosynthesis and reaction prediction
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
Don't Change Me! User-Controllable Selective Paraphrase Generation
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.
Rapid Adaptation of BERT for Information Extraction on Domain-Specific Business Documents
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.
