Pages that link to "Item:Q465707"
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The following pages link to A reduced adjoint approach to variational data assimilation (Q465707):
Displaying 18 items.
- Hybrid nested sampling algorithm for Bayesian model selection applied to inverse subsurface flow problems (Q348583) (← links)
- POD/DEIM reduced-order strategies for efficient four dimensional variational data assimilation (Q350095) (← links)
- Reduced order modeling for accelerated Monte Carlo simulations in radiation transport (Q669681) (← links)
- Parameterised non-intrusive reduced order methods for ensemble Kalman filter data assimilation (Q1626167) (← links)
- A variational approach for parameter estimation based on balanced proper orthogonal decomposition (Q1986731) (← links)
- Attention-based convolutional autoencoders for 3D-variational data assimilation (Q2020890) (← links)
- Feasibility of DEIM for retrieving the initial field via dimensionality reduction (Q2120024) (← links)
- A metric tensor approach to data assimilation with adaptive moving meshes (Q2157134) (← links)
- A note on domain decomposition approaches for solving 3D variational data assimilation models (Q2281542) (← links)
- A multilevel approach for computing the limited-memory Hessian and its inverse in variational data assimilation (Q2821785) (← links)
- Efficient identification of uncertain parameters in a large-scale tidal model of the European continental shelf by proper orthogonal decomposition (Q2900441) (← links)
- Adjoint to the Hessian derivative and error covariances in variational data assimilation (Q2999547) (← links)
- Efficiency of a POD-based reduced second-order adjoint model in 4D-Var data assimilation (Q3422078) (← links)
- A reduced-order approach to four-dimensional variational data assimilation using proper orthogonal decomposition (Q3437052) (← links)
- First-order and second-order adjoint methods for parameter identification problems with an application to the elasticity imaging inverse problem (Q4638156) (← links)
- Adjoint implementation of Rosenbrock methods applied to variational data assimilation problems. (Q5928905) (← links)
- Numerical linear algebra in data assimilation (Q6068266) (← links)
- Accelerating inverse inference of ensemble Kalman filter via reduced-order model trained using adaptive sparse observations (Q6117701) (← links)
