172 citations · 516 across the 28 of their papers we have counts for
Showing 2020 · eess.SPShow all
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eess.SP2020★ 67 cited
Graph Signal Processing and Deep Learning: Convolution, Pooling, and Topology
Mark Cheung, John Shi, Oren Wright +3
Deep learning, particularly convolutional neural networks (CNNs), have yielded rapid, significant improvements in computer vision and related domains. But conventional deep learnin…
eess.SP2020
Pooling in Graph Convolutional Neural Networks
Mark Cheung, John Shi, Lavender Yao Jiang +2
Graph convolutional neural networks (GCNNs) are a powerful extension of deep learning techniques to graph-structured data problems. We empirically evaluate several pooling methods…
eess.SP2020★ 49 cited
Graph Fourier Transform: A Stable Approximation
João Domingos, José M. F. Moura
In Graph Signal Processing (GSP), data dependencies are represented by a graph whose nodes label the data and the edges capture dependencies among nodes. The graph is represented b…