Graph Signal Processing
PulseAugur coverage of Graph Signal Processing — every cluster mentioning Graph Signal Processing across labs, papers, and developer communities, ranked by signal.
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New framework for processing heterogeneous network signals introduced
Researchers have introduced a novel framework for processing heterogeneous network signals called Sheaf-theoretic Signal Processing on Graphs (SSP). This approach utilizes network sheaves to model diverse local signal s…
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New framework for subgraph filter learning addresses incomplete graph data
Researchers have introduced a novel framework called Subgraph Filter Learning (SFL) to address challenges in graph signal processing where complete graph topology is often unavailable. This framework proposes using subg…
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New method models graph changes as low-rank updates for signal interpolation
Researchers have developed a novel method for spatial-temporal signal interpolation by modeling changes in graph adjacency matrices as low-rank updates. This approach allows for the representation of slowly time-varying…
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Topological Signal Processing tutorial bridges theory and applications
Researchers have introduced Topological Signal Processing (TSP) as a generalization of Graph Signal Processing (GSP) to analyze complex datasets. TSP extends signal analysis beyond nodes to edges and higher-dimensional …