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cs.LG2021
Nonlinearities in Steerable SO(2)-Equivariant CNNs
Daniel Franzen, Michael Wand
Invariance under symmetry is an important problem in machine learning. Our paper looks specifically at equivariant neural networks where transformations of inputs yield homomorphic…
cs.LG2019
Progressive Stochastic Binarization of Deep Networks
David Hartmann, Michael Wand
A plethora of recent research has focused on improving the memory footprint and inference speed of deep networks by reducing the complexity of (i) numerical representations (for ex…