Machine-learned state space model for joint forecasting
US12217144B2 · kind B2 · utility
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Key dates
| Filing date | Aug 31, 2020 |
| Grant date | Feb 4, 2025 |
| Priority date | — |
| Expiry date | Dec 7, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/044
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A deep state space generative model is augmented with intervention prediction. The state space model provides a principled way to capture the interactions among observations, interventions, critical event occurrences, true states, and associated uncertainty. The state space model can include a discrete-time hazard rate model that provides flexible fitting of general survival time distributions. The state space model can output a joint prediction of event risk, observation and intervention trajectories based on patterns in temporal progressions, and correlations between past measurements and interventions.
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