Random walk visit and length statistics, especially from self-avoiding walks, classify diverse network datasets more accurately than several established feature extraction baselines.
A graph convolutional neural network for classification of building patterns using spatial vector data.ISPRS Journal of Photogrammetry and Remote Sensing, 150:259– 273, 2019
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Network classification through random walks
Random walk visit and length statistics, especially from self-avoiding walks, classify diverse network datasets more accurately than several established feature extraction baselines.