Abstract: Recently, polynomial graph filter learning (PGFL) has demonstrated promising performance for modeling graph signals in Graph Neural Networks (GNNs) on both homophilic and heterophilic graphs ...
Dr Bahman Kalantari discusses a piece of software that he has developed through his research into polynomial root-finding. With this software, users can explore the world of polynomials and their ...
Abstract: Spectral graph filters are a key component in state-of-the-art machine learning models used for graph-based learning, such as graph neural networks. For certain tasks stability of the ...
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