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Found 2 papers, 1 papers with code
Learning Graph ARMA Processes from Time-Vertex Spectra
The modeling of time-varying graph signals as stationary time-vertex stochastic processes permits the inference of missing signal values by efficiently employing the correlation patterns of the process across different graph nodes and time instants.
Graph Domain Adaptation with Localized Graph Signal Representations
We estimate the unknown target labels by solving an optimization problem where the label information is transferred from the source graph to the target graph based on the prior that the projections of the label functions onto localized graph bases be similar between the source and the target graphs.
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