Abstract: Hypergraph Neural Networks (HGNNs) are increasingly utilized to analyze complex inter-entity relationships. Traditional HGNN systems, based on a hyperedge-centric dataflow model, ...
A new machine learning method has achieved what even AlphaFold cannot — the design of intrinsically disordered proteins (IDPs), the shape-shifting biomolecules that make up nearly 30% of all human ...
Abstract: Existing message passing-based and transformer-based graph neural networks (GNNs) cannot satisfy requirements for learning representative graph embeddings due to restricted receptive fields, ...
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