Sparse Diffusion-Convolutional Neural Networks

Abstract

The predictive power and overall computational efficiency of Diffusionconvolutional neural networks make them an attractive choice for node classification tasks. However, a naive dense-tensor-based implementation of DCNNs leads to O(N) memory complexity which is prohibitive for large graphs. In this paper, we introduce a simple method for thresholding input… (More)

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