-
公开(公告)号:US12056615B2
公开(公告)日:2024-08-06
申请号:US17030361
申请日:2020-09-23
Applicant: QUALCOMM Technologies, Inc.
Inventor: Berkay Kicanaoglu , Taco Sebastiaan Cohen , Pim De Haan
Abstract: A method for generating a convolutional neural network to operate on a spherical manifold, generates locally-defined gauges at multiple positions on the spherical manifold. A convolution is defined at each of the positions on the spherical manifold with respect to an arbitrarily selected locally-defined gauge. The results of the convolution that is defined at each position based on gauge equivariance is translated to obtain a manifold convolution.
-
公开(公告)号:US12158922B2
公开(公告)日:2024-12-03
申请号:US17169338
申请日:2021-02-05
Applicant: QUALCOMM TECHNOLOGIES, INC.
Inventor: Pim De Haan , Maurice Weiler , Taco Sebastiaan Cohen , Max Welling
IPC: G06F17/10 , G06F17/14 , G06N3/08 , G06N7/01 , G06V10/426 , G06V10/44 , G06V10/764 , G06V10/82
Abstract: Certain aspects of the present disclosure provide a method for performing machine learning, comprising: determining a plurality of vertices in a neighborhood associated with a mesh including a target vertex; determining a linear transformation configured to parallel transport signals along all edges in the mesh to the target vertex; applying the linear transformation to the plurality of vertices in the neighborhood to form a combined signal at the target vertex; determining a set of basis filters; linearly combining the basis filters using a set of learned parameters to form a gauge equivariant convolution filter, wherein the gauge equivariant convolution filter is constrained to maintain gauge equivariance; applying the gauge equivariant convolution filter to the combined signal to form an intermediate output; and applying a nonlinearity to the intermediate output to form a convolution output.
-