Representing a neural network utilizing paths within the network to improve a performance of the neural network
US11507846B2 · kind B2 · utility
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18Claims
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Key dates
| Filing date | Mar 13, 2019 |
| Grant date | Nov 22, 2022 |
| Priority date | — |
| Expiry date | Aug 19, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/092
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Artificial neural networks (ANNs) are computing systems that imitate a human brain by learning to perform tasks by considering examples. By representing an artificial neural network utilizing individual paths each connecting an input of the ANN to an output of the ANN, a complexity of the ANN may be reduced, and the ANN may be trained and implemented in a much faster manner when compared to an implementation using fully connected ANN graphs.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.