199 citations · 278 across the 8 of their papers we have counts for
4 papers · 1 filter
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…
Dynamic Few-Shot Visual Learning without Forgetting
Spyros Gidaris, Nikos Komodakis
The human visual system has the remarkably ability to be able to effortlessly learn novel concepts from only a few examples. Mimicking the same behavior on machine learning vision…
Unsupervised Representation Learning by Predicting Image Rotations
Spyros Gidaris, Praveer Singh, Nikos Komodakis
Over the last years, deep convolutional neural networks (ConvNets) have transformed the field of computer vision thanks to their unparalleled capacity to learn high level semantic…
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…