Shaping a neural network architecture utilizing learnable sampling layers
US11710042B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 5, 2020 |
| Grant date | Jul 25, 2023 |
| Priority date | — |
| Expiry date | Oct 3, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to shaping the architecture of a neural network. For example, the disclosed systems can provide a neural network shaping mechanism for at least one sampling layer of a neural network. The neural network shaping mechanism can include a learnable scaling factor between a sampling rate of the at least one sampling layer and an additional sampling function. The disclosed systems can learn the scaling factor based on a dataset while jointly learning the network weights of the neural network. Based on the learned scaling factor, the disclosed systems can shape the architecture of the neural network by modifying the sampling rate of the at least one sampling layer.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.