Advancing Topological Deep Learning for Complex Relational Systems

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This presentation provides a comprehensive overview of Topological Deep Learning, emphasizing its advancement beyond traditional pairwise interactions to utilize complex topological structures. It introduces concepts such as neural networks applied to sets, graphs, and hypergraphs, and explains the computational processes of message passing within these frameworks. We explore various architectures including Hypergraph, Simplicial, and Cellular Networks, and demonstrate their application in...