Invention Application
- Patent Title: MULTI-LAYER NEURAL NETWORKS USING SYMMETRIC TENSORS
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Application No.: US17526628Application Date: 2021-11-15
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Publication No.: US20220147800A1Publication Date: 2022-05-12
- Inventor: Julio ZAMORA ESQUIVEL , Hector CORDOURIER MARURI , Jose CAMACHO PEREZ , Paulo LOPEZ MEYER , Jesus Adan CRUZ VARGAS
- Applicant: Intel Corporation
- Applicant Address: US CA Santa Clara
- Assignee: Intel Corporation
- Current Assignee: Intel Corporation
- Current Assignee Address: US CA Santa Clara
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06N3/08

Abstract:
Methods and apparatuses for implementing a neural network using symmetric tensors. In embodiments, a system may include a higher order neural network with a plurality of layers that includes an input layer, one or more hidden layers, and an output layer. Each of the input layer, the one or more hidden layers, and the output layer includes a plurality of neurons, where the plurality of neurons includes at least first order neurons and second order neurons, and where inputs at a second order neuron are combined using a symmetric tensor.
Public/Granted literature
- US12067477B2 Multi-layer neural networks using symmetric tensors Public/Granted day:2024-08-20
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