1 code implementation • 22 Apr 2024 • Mauricio Lima, Katherine Deck, Oliver R. A. Dunbar, Tapio Schneider
Training of such a model over the continental United States has demonstrated that a single set of model parameters can be used across independent catchments, and that RNNs can outperform physics-based models.
1 code implementation • 29 Dec 2023 • Jin-Long Wu, Matthew E. Levine, Tapio Schneider, Andrew Stuart
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, yet they are dynamically important.
no code implementations • 17 Aug 2023 • Miguel Liu-Schiaffini, Clare E. Singer, Nikola Kovachki, Tapio Schneider, Kamyar Azizzadenesheli, Anima Anandkumar
Tipping points are abrupt, drastic, and often irreversible changes in the evolution of non-stationary and chaotic dynamical systems.
1 code implementation • 2 Feb 2021 • Daniel Z. Huang, Tapio Schneider, Andrew M. Stuart
In this paper, we work with the ExKI, EKI, and a variant on EKI which we term unscented Kalman inversion (UKI).
Numerical Analysis Numerical Analysis Dynamical Systems
no code implementations • 24 Dec 2020 • Oliver R. A. Dunbar, Alfredo Garbuno-Inigo, Tapio Schneider, Andrew M. Stuart
Here we demonstrate an approach to model calibration and uncertainty quantification that requires only $O(10^2)$ model runs and can accommodate internal climate variability.
Gaussian Processes Statistics Theory Statistics Theory
no code implementations • 31 Aug 2017 • Tapio Schneider, Shiwei Lan, Andrew Stuart, João Teixeira
Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems.