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Found 4 papers, 1 papers with code
UAlign: Pushing the Limit of Template-free Retrosynthesis Prediction with Unsupervised SMILES Alignment
Single-step retrosynthesis prediction, a crucial step in the planning process, has witnessed a surge in interest in recent years due to advancements in AI for science.
A Synchronized Layer-by-layer Growing Approach for Plausible Neuronal Morphology Generation
Neuronal morphology is essential for studying brain functioning and understanding neurodegenerative disorders.
Advective Diffusion Transformers for Topological Generalization in Graph Learning
Graph diffusion equations are intimately related to graph neural networks (GNNs) and have recently attracted attention as a principled framework for analyzing GNN dynamics, formalizing their expressive power, and justifying architectural choices.
Molecule Generation for Drug Design: a Graph Learning Perspective
Machine learning, particularly graph learning, is gaining increasing recognition for its transformative impact across various fields.
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