Chemical Reaction Prediction
7 papers with code • 1 benchmarks • 1 datasets
Most implemented papers
Molecular Transformer - A Model for Uncertainty-Calibrated Chemical Reaction Prediction
Organic synthesis is one of the key stumbling blocks in medicinal chemistry.
Chemical-Reaction-Aware Molecule Representation Learning
Molecule representation learning (MRL) methods aim to embed molecules into a real vector space.
Root-aligned SMILES: A Tight Representation for Chemical Reaction Prediction
Chemical reaction prediction, involving forward synthesis and retrosynthesis prediction, is a fundamental problem in organic synthesis.
A generalized-template-based graph neural network for accurate organic reactivity prediction
In addition to the built-in interpretability of the generalized reaction templates, the high score–accuracy correlation of the model allows users to assess the uncertainty of the machine predictions.
Graph Neural Networks-based Hybrid Framework For Predicting Particle Crushing Strength
Therefore, we firstly generate a dataset with 45, 000 numerical simulations and 900 particle types to facilitate the research progress of machine learning for particle crushing.
ReLM: Leveraging Language Models for Enhanced Chemical Reaction Prediction
Predicting chemical reactions, a fundamental challenge in chemistry, involves forecasting the resulting products from a given reaction process.
A Self-feedback Knowledge Elicitation Approach for Chemical Reaction Predictions
The task of chemical reaction predictions (CRPs) plays a pivotal role in advancing drug discovery and material science.