Graph Classification with 2D Convolutional Neural Networks

ICLR 2018 Antoine Jean-Pierre Tixier • Giannis Nikolentzos • Polykarpos Meladianos • Michalis Vazirgiannis

Graph learning is currently dominated by graph kernels, which, while powerful, suffer some significant limitations. Convolutional Neural Networks (CNNs) offer a very appealing alternative, but processing graphs with CNNs is not trivial. To address this challenge, many sophisticated extensions of CNNs have recently been introduced.

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