2 papers
cs.LG2020
Geometric graphs from data to aid classification tasks with graph convolutional networks
Yifan Qian, Paul Expert, Pietro Panzarasa +1
Traditional classification tasks learn to assign samples to given classes based solely on sample features. This paradigm is evolving to include other sources of information, such a…
cs.LG2019
Quantifying the Alignment of Graph and Features in Deep Learning
Yifan Qian, Paul Expert, Tom Rieu +2
We show that the classification performance of graph convolutional networks (GCNs) is related to the alignment between features, graph, and ground truth, which we quantify using a…