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20152026
most citedPaying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer

1.6k citations · 2k across the 13 of their papers we have counts for

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Showing 2018 · cs.LGShow all

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cs.LG2018

Scattering Networks for Hybrid Representation Learning

Edouard Oyallon, Sergey Zagoruyko, Gabriel Huang +4

Scattering networks are a class of designed Convolutional Neural Networks (CNNs) with fixed weights. We argue they can serve as generic representations for modelling images. In par…

cs.LG2018

GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders

Martin Simonovsky, Nikos Komodakis

Deep learning on graphs has become a popular research topic with many applications. However, past work has concentrated on learning graph embedding tasks, which is in contrast with…