Cornell Researchers Introduce Graph Mamba Networks (GMNs): A General Framework for a New Class of Graph Neural Networks Based on Selective State Space Models

Graph-based machine learning is undergoing a significant transformation, largely propelled by the introduction of Graph Neural Networks (GNNs). These networks have been pivotal in harnessing the complexity of graph-structured data, offering innovative solutions across various domains. Despite their initial success, traditional GNNs face critical challenges, particularly those relying on local message-passing mechanisms. They need help […]

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