A causation-based computationally efficient strategy for deploying Lagrangian drifters to improve real-time state estimation
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Publication:6584213
DOI10.1016/j.physd.2024.134283MaRDI QIDQ6584213
Nan Chen, Stephen Wiggins, E. M. Bollt
Publication date: 6 August 2024
Published in: Physica D (Search for Journal in Brave)
Numerical mathematical programming methods (65K05) Numerical optimization and variational techniques (65K10) Approximation methods and numerical treatment of dynamical systems (37M99) Causal inference from observational studies (62D20)
Cites Work
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- An introduction to turbulent dynamical systems in complex systems
- Lagrangian descriptors: a method for revealing phase space structures of general time dependent dynamical systems
- Lessons in uncertainty quantification for turbulent dynamical systems
- Filtering nonlinear spatio-temporal chaos with autoregressive linear stochastic models
- Quantifying Bayesian filter performance for turbulent dynamical systems through information theory
- Lagrangian data assimilation for river hydraulics simulations
- Information theory and dynamical system predictability
- Non-Gaussian test models for prediction and state estimation with model errors
- Feasibility of DEIM for retrieving the initial field via dimensionality reduction
- Learning nonlinear turbulent dynamics from partial observations via analytically solvable conditional statistics
- An efficient and statistically accurate Lagrangian data assimilation algorithm with applications to discrete element sea ice models
- Lagrangian descriptors and the action integral of classical mechanics
- Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning
- Noisy Lagrangian tracers for filtering random rotating compressible flows
- Sequentially optimal sensor placement in thermoelastic models for real time applications
- Unsteady flow sensing and estimation via the gappy proper orthogonal decomposition
- A New Selection Operator for the Discrete Empirical Interpolation Method---Improved A Priori Error Bound and Extensions
- Quantifying uncertainty for predictions with model error in non-Gaussian systems with intermittency
- Information barriers for noisy Lagrangian tracers in filtering random incompressible flows
- A Theoretical Framework for Lagrangian Descriptors
- Lagrangian data assimilation for point vortex systems
- Lagrangian Analysis and Prediction of Coastal and Ocean Dynamics
- Filtering nonlinear dynamical systems with linear stochastic models
- Stochastic forcing of the linearized Navier–Stokes equations
- Atmospheric and Oceanic Fluid Dynamics
- Accuracy of Some Approximate Gaussian Filters for the Navier--Stokes Equation in the Presence of Model Error
- Link between statistical equilibrium fidelity and forecasting skill for complex systems with model error
- Data-driven prediction of multistable systems from sparse measurements
- Data-Driven Sparse Sensor Placement for Reconstruction: Demonstrating the Benefits of Exploiting Known Patterns
- An Information Criterion for Choosing Observation Locations in Data Assimilation and Prediction
- Shallow neural networks for fluid flow reconstruction with limited sensors
- How entropic regression beats the outliers problem in nonlinear system identification
- Sparse Sensing and DMD-Based Identification of Flow Regimes and Bifurcations in Complex Flows
- Data assimilation: Mathematical and statistical perspectives
- Information Theory and Stochastics for Multiscale Nonlinear Systems
- On Information and Sufficiency
- Uncertainty quantification of nonlinear Lagrangian data assimilation using linear stochastic forecast models
- Launching Drifter Observations in the Presence of Uncertainty
- Stochastic Methods for Modeling and Predicting Complex Dynamical Systems
- Entropic regression with neurologically motivated applications
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