Retrosynthesis prediction is crucial in organic synthesis and drug discovery, aiding chemists
in designing efficient synthetic routes for target molecules. Data-driven deep retrosynthesis …

Recently, template-based (TB) and template-free (TF) molecule graph learning methods
have shown promising results to retrosynthesis. TB methods are more accurate using pre …

Graph neural networks (GNNs) have been demonstrated as a powerful tool for analyzing
non-Euclidean graph data. However, the lack of efficient distributed graph learning systems …

A fundamental technique of recommender systems involves modeling user preferences,
where queries and items are widely used as symbolic representations of user interests …