System and method for deep enriched neural networks for time series forecasting
US12223399B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 28, 2020 |
| Grant date | Feb 11, 2025 |
| Priority date | — |
| Expiry date | Dec 14, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/0985
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present teaching relates to method, system, medium, and implementations for machine learning. Upon receiving input data associated with a time series, hidden representations associated with the time series in a feature space are obtained and used to generate a query vector in a query space. Such generated query vector is then used to query relevant historic information related to the time series. The query vector and the relevant historic information are aggregated to generate at least one queried vector, which is aggregated with the hidden representations to generate enriched hidden representations that enhance the expressiveness of the hidden representations.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.