Leveraging arbitrary mobile sensor trajectories with shallow recurrent decoder networks for full-state reconstruction

no code implementations • 20 Jul 2023 • Megan R. Ebers, Jan P. Williams, Katherine M. Steele, J. Nathan Kutz

Sensing is one of the most fundamental tasks for the monitoring, forecasting and control of complex, spatio-temporal systems.

Discrepancy Modeling Framework: Learning missing physics, modeling systematic residuals, and disambiguating between deterministic and random effects

1 code implementation • 10 Mar 2022 • Megan R. Ebers, Katherine M. Steele, J. Nathan Kutz

We introduce a discrepancy modeling framework to identify the missing physics and resolve the model-measurement mismatch with two distinct approaches: (i) by learning a model for the evolution of systematic state-space residual, and (ii) by discovering a model for the deterministic dynamical error.

GPR Model Discovery