Covariate processing with neural network execution blocks
US12406173B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 30, 2020 |
| Grant date | Sep 2, 2025 |
| Priority date | — |
| Expiry date | Feb 5, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/096
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for forecasting future values of a target variable using past values thereof, the values of the target variable being affected by one or more covariates wherein the covariates are independent from the target variable. The method comprises using a covariate-specific AI model, computing a covariate effect of the covariates on the target variable. The covariates effect is a defined modification to the values of the target variable caused by the covariates. The method also comprises computing intrinsic past values of the target variable by removing the covariate effect of the covariates from past values of the target variable. The method further comprises using a target-variable-specific AI model, generating an intrinsic forecast of the future values of the target variable; and computing a forecast that includes the covariate effect using the intrinsic forecast of the future values of the target variable and the covariate effect.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.