Invention Grant
- Patent Title: Convolutional layers for neural networks using programmable nanophotonics
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Application No.: US16412261Application Date: 2019-05-14
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Publication No.: US12033065B2Publication Date: 2024-07-09
- Inventor: Tyler Kenney , Martin Forsythe , Tomo Lazovich , Darius Bunandar
- Applicant: Lightmatter, Inc.
- Applicant Address: US MA Boston
- Assignee: Lightmatter, Inc.
- Current Assignee: Lightmatter, Inc.
- Current Assignee Address: US MA Boston
- Agency: Wolf, Greenfield & Sacks, P.C.
- Main IPC: G06N3/063
- IPC: G06N3/063 ; G06F17/16 ; G06N3/04 ; G06N3/045 ; G06N3/067 ; G06N3/08

Abstract:
Aspects of the present application relate to techniques for computing convolutions and cross-correlations of input matrices. A first technique is based on the transformation of convolution operations into a matrix-vector product. A second technique is based on two-dimensional matrix multiplication. A third technique is based on the convolution theorem, which states that convolutions correspond to multiplications in a transform space.
Embodiments include methods for computing convolutions of a filter matrix and an input data matrix; apparatuses for computing convolutions of a filter matrix and an input data matrix; and a non-transitory computer readable medium programmed with instructions that, when executed by a processor perform a method for computing convolutions of a filter matrix and an input data matrix.
Embodiments include methods for computing convolutions of a filter matrix and an input data matrix; apparatuses for computing convolutions of a filter matrix and an input data matrix; and a non-transitory computer readable medium programmed with instructions that, when executed by a processor perform a method for computing convolutions of a filter matrix and an input data matrix.
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