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PGC-DGCNN
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
PGC-DGCNN provides a new definition of graph convolutional filter. It generalizes the most commonly adopted filter, adding an hyper-parameter controlling the distance of the considered neighborhood. The model extends graph convolutions, following an intuition derived from the well-known convolutional filters over multi-dimensional tensors. The methods involves a simple, efficient and effective way to introduce a hyper-parameter on graph convolutions that influences the filter size, i.e. its receptive field over the considered graph.
Description and image from: On Filter Size in Graph Convolutional Networks
Papers archive 2025-07-28
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On Filter Size in Graph Convolutional Networks 23 Nov 2018 · 1 repository · arXiv:1811.10435
Tasks archive 2025-07-28
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Usage over time archive 2025-07-28
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Categories archive 2025-07-28
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