
Finite Impulse Response Filters for Simplicial Complexes
In this paper, we study linear filters to process signals defined on sim...
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GraphTime Convolutional Neural Networks
Spatiotemporal data can be represented as a process over a graph, which ...
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Nonlinear StateSpace Generalizations of Graph Convolutional Neural Networks
Graph convolutional neural networks (GCNNs) learn compositional represen...
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Online TimeVarying Topology Identification via PredictionCorrection Algorithms
Signal processing and machine learning algorithms for data supported ove...
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Stochastic Graph Neural Networks
Graph neural networks (GNNs) model nonlinear representations in graph da...
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Forecasting MultiDimensional Processes over Graphs
The forecasting of multivariate time processes through graphbased tech...
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Quantization Analysis and Robust Design for Distributed Graph Filters
Distributed graph filters have found applications in wireless sensor net...
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Graphs, Convolutions, and Neural Networks
Network data can be conveniently modeled as a graph signal, where data v...
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EdgeNets:Edge Varying Graph Neural Networks
Driven by the outstanding performance of neural networks in the structur...
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Generalizing Graph Convolutional Neural Networks with EdgeVariant Recursions on Graphs
This paper reviews graph convolutional neural networks (GCNNs) through t...
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On the Transferability of Spectral Graph Filters
This paper focuses on spectral filters on graphs, namely filters defined...
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Autoregressive Moving Average Graph Filtering
One of the cornerstones of the field of signal processing on graphs are ...
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Elvin Isufi
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