A Probabilistic Approach to Learning the Degree of Equivariance in Steerable CNNs

Lars Veefkind, Gabriele Cesa

Steerable convolutional neural networks (SCNNs) enhance task performance by modelling geometric symmetries through equivariance constraints on weights. Yet, unknown or varying symm…