12 citations · 12 across the 2 of their papers we have counts for
2 papers
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.SP2019★ 12 cited
Graph Signal Processing: Modulation, Convolution, and Sampling
John Shi, Jose M. F. Moura
To analyze data supported by arbitrary graphs G, DSP has been extended to Graph Signal Processing (GSP) by redefining traditional DSP concepts like shift, filtering, and Fourier tr…