AdaGCN applies AdaBoost to combine non-linear classifiers trained on A^l X features from each hop, achieving state-of-the-art node classification on several benchmarks while avoiding the oversmoothing that limits deep GCN stacks.
Spectral networks and locally connected networks on graphs
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AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models
AdaGCN applies AdaBoost to combine non-linear classifiers trained on A^l X features from each hop, achieving state-of-the-art node classification on several benchmarks while avoiding the oversmoothing that limits deep GCN stacks.