570 citations · 3k across the 41 of their papers we have counts for
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3 papers · 1 filter
cs.LG2016★ 21 cited
Steerable CNNs
Taco S. Cohen, Max Welling
It has long been recognized that the invariance and equivariance properties of a representation are critically important for success in many vision tasks. In this paper we present…
cs.CV2016★ 25 cited
A New Method to Visualize Deep Neural Networks
Luisa M. Zintgraf, Taco S. Cohen, Max Welling
We present a method for visualising the response of a deep neural network to a specific input. For image data for instance our method will highlight areas that provide evidence in…
cs.LG2016★ 552 cited
Group Equivariant Convolutional Networks
Taco S. Cohen, Max Welling
We introduce Group equivariant Convolutional Neural Networks (G-CNNs), a natural generalization of convolutional neural networks that reduces sample complexity by exploiting symmet…