Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs

CVPR 2017 Martin SimonovskyNikos Komodakis

A number of problems can be formulated as prediction on graph-structured data. In this work, we generalize the convolution operator from regular grids to arbitrary graphs while avoiding the spectral domain, which allows us to handle graphs of varying size and connectivity... (read more)

PDF Abstract

Evaluation results from the paper


  Submit results from this paper to get state-of-the-art GitHub badges and help community compare results to other papers.