Patent ID: 11934478
Assignee: THE UNIVERSITY OF CHICAGO
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method, carried out by a computing device, for computationally processing data with a multi-layer convolutional neural network (CNN) implemented in the computing device and having an input layer, an output layer, and one or more intermediate layers, the method comprising:
at the computing device, receiving digital image data corresponding to input data that are represented in a form of evaluations of one or more continuous functions on a sphere;
inputting the input data to the input layer;
computing outputs of the input layer as covariant Fourier space activations by analytically transforming the one or more continuous functions into spherical harmonic expansions of the data;
processing the covariant Fourier activations from the input layer sequentially through each of the one or more intermediate layers of the CNN, from the first intermediate layer to the last intermediate layer, wherein each intermediate layer is configured to apply Clebsch-Gordan transforms to compute respective covariant Fourier space activations as input to an immediately next layer of the CNN, without computing any intermediate inverse Fourier transforms or forward Fourier transforms; and
processing the respective covariant Fourier space activations of the last intermediate layer in the output layer of the CNN to compute invariant activations.