9 citations · 16 across the 3 of their papers we have counts for
3 papers
Learning About Structural Errors in Models of Complex Dynamical Systems
Jin-Long Wu, Matthew E. Levine, Tapio Schneider +1
Complex dynamical systems are notoriously difficult to model because some degrees of freedom (e.g., small scales) may be computationally unresolvable or are incompletely understood…
Ensemble Kalman Inversion for Sparse Learning of Dynamical Systems from Time-Averaged Data
Tapio Schneider, Andrew M. Stuart, Jin-Long Wu
Enforcing sparse structure within learning has led to significant advances in the field of data-driven discovery of dynamical systems. However, such methods require access not only…
Learning Stochastic Closures Using Ensemble Kalman Inversion
Tapio Schneider, Andrew M. Stuart, Jin-Long Wu
Although the governing equations of many systems, when derived from first principles, may be viewed as known, it is often too expensive to numerically simulate all the interactions…