Pages that link to "Item:Q5451329"
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The following pages link to Data assimilation: Mathematical and statistical perspectives (Q5451329):
Displaying 29 items.
- Can local particle filters beat the curse of dimensionality? (Q81243) (← links)
- Analysis of the 3DVAR filter for the partially observed Lorenz '63 model (Q379784) (← links)
- Absolutely minimising generalised solutions to the equations of vectorial calculus of variations in \(L^\infty \) (Q522460) (← links)
- Solving ill-posed image processing problems using data assimilation (Q625544) (← links)
- Optimal strategies for the control of autonomous vehicles in data assimilation (Q1691207) (← links)
- Adaptive modeling, adaptive data assimilation and adaptive sampling (Q2371208) (← links)
- Deterministic mean-field ensemble Kalman filtering (Q2805009) (← links)
- Visualization for large-scale Gaussian updates (Q2835315) (← links)
- Variational data assimilation using targetted random walks (Q2900440) (← links)
- ‘Intractable and unsolved’: some thoughts on statistical data assimilation with uncertain static parameters (Q2955508) (← links)
- Analysis of the Data Assimilation Methods from the Mathematical Point of View (Q2961427) (← links)
- Stochastic modelling of urban structure (Q4557688) (← links)
- Almost Sure Error Bounds for Data Assimilation in Dissipative Systems with Unbounded Observation Noise (Q4562433) (← links)
- Book Reviews (Q4592952) (← links)
- Modern Koopman Theory for Dynamical Systems (Q5075835) (← links)
- Principles of Data Assimilation (Q5086254) (← links)
- On Bayesian data assimilation for PDEs with ill-posed forward problems (Q5089412) (← links)
- Data Assimilation (Q5261548) (← links)
- Decreasing Flow Uncertainty in Bayesian Inverse Problems Through Lagrangian Drifter Control (Q5272911) (← links)
- Chapter 1: Introduction to data assimilation and inverse problems (Q5346762) (← links)
- Bayesian inversion techniques for stochastic partial differential equations (Q6059574) (← links)
- Numerical linear algebra in data assimilation (Q6068266) (← links)
- Uncertainty quantification of nonlinear Lagrangian data assimilation using linear stochastic forecast models (Q6115350) (← links)
- Efficient deep data assimilation with sparse observations and time-varying sensors (Q6198151) (← links)
- Launching Drifter Observations in the Presence of Uncertainty (Q6444907) (← links)
- Variational data assimilation and its decoupled iterative numerical algorithms for Stokes-Darcy model (Q6491441) (← links)
- Lagrangian descriptors with uncertainty (Q6584212) (← links)
- A causation-based computationally efficient strategy for deploying Lagrangian drifters to improve real-time state estimation (Q6584213) (← links)
- On the recovery of initial status for linearized shallow-water wave equation by data assimilation with error analysis (Q6660073) (← links)
