The following pages link to Data Assimilation (Q5261548):
Displaying 50 items.
- Bayesian parameter estimation for the Swift model of eye-movement control during reading (Q2177484) (← links)
- Convergence rates of Gaussian ODE filters (Q2209738) (← links)
- Error analysis of fully discrete mixed finite element data assimilation schemes for the Navier-Stokes equations (Q2216608) (← links)
- Localised sequential state estimation for advection dominated flows with non-Gaussian uncertainty description (Q2220577) (← links)
- Data assimilation for models with parametric uncertainty (Q2222452) (← links)
- A data-driven non-linear assimilation framework with neural networks (Q2225345) (← links)
- Sequential data assimilation of the stochastic SEIR epidemic model for regional COVID-19 dynamics (Q2227162) (← links)
- Bayesian approach to inverse time-harmonic acoustic obstacle scattering with phaseless data generated by point source waves (Q2246258) (← links)
- Spatial localization for nonlinear dynamical stochastic models for excitable media (Q2286234) (← links)
- Linearized filtering of affine processes using stochastic Riccati equations (Q2289789) (← links)
- Discrete gradients for computational Bayesian inference (Q2297877) (← links)
- A non-intrusive reduced basis EKI for time fractional diffusion inverse problems (Q2300550) (← links)
- Strong convergence rates of probabilistic integrators for ordinary differential equations (Q2302455) (← links)
- The parameter Houlihan: a solution to high-throughput identifiability indeterminacy for brutally ill-posed problems (Q2328494) (← links)
- Ergodicity and accuracy of optimal particle filters for Bayesian data assimilation (Q2335868) (← links)
- Optimization based methods for partially observed chaotic systems (Q2420632) (← links)
- Low-rank statistical finite elements for scalable model-data synthesis (Q2671375) (← links)
- Iterated Kalman methodology for inverse problems (Q2671376) (← links)
- Data assimilation with model error: analytical and computational study for sabra shell model (Q2677779) (← links)
- Iterate averaging, the Kalman filter, and 3DVAR for linear inverse problems (Q2679818) (← links)
- Deep learning-enhanced ensemble-based data assimilation for high-dimensional nonlinear dynamical systems (Q2681144) (← links)
- Influence sampling of trailing variables of dynamical systems (Q2681722) (← links)
- Long-time asymptotics of the filtering distribution for partially observed chaotic dynamical systems (Q2801321) (← links)
- Deterministic mean-field ensemble Kalman filtering (Q2805009) (← links)
- Multilevel ensemble Kalman filtering (Q2814458) (← links)
- Analysis of the Data Assimilation Methods from the Mathematical Point of View (Q2961427) (← links)
- Multilevel Sequential Monte Carlo with Dimension-Independent Likelihood-Informed Proposals (Q3176244) (← links)
- Long-Time Stability and Accuracy of the Ensemble Kalman--Bucy Filter for Fully Observed Processes and Small Measurement Noise (Q3176261) (← links)
- Optimal Reduced Model Algorithms for Data-Based State Estimation (Q3386988) (← links)
- Bayesian approach to a nonlinear inverse problem for a time-space fractional diffusion equation (Q4555031) (← links)
- Projected Shadowing-Based Data Assimilation (Q4562414) (← links)
- Almost Sure Error Bounds for Data Assimilation in Dissipative Systems with Unbounded Observation Noise (Q4562433) (← links)
- Ensemble-marginalized Kalman filter for linear time-dependent PDEs with noisy boundary conditions: application to heat transfer in building walls (Q4571011) (← links)
- A Strongly Convergent Numerical Scheme from Ensemble Kalman Inversion (Q4581770) (← links)
- Book Reviews (Q4592952) (← links)
- The cardiovascular system: Mathematical modelling, numerical algorithms and clinical applications (Q4594245) (← links)
- Multilevel Particle Filters (Q4599144) (← links)
- Bayesian Static Parameter Estimation for Partially Observed Diffusions via Multilevel Monte Carlo (Q4610146) (← links)
- Random Forward Models and Log-Likelihoods in Bayesian Inverse Problems (Q4611529) (← links)
- Accuracy of Some Approximate Gaussian Filters for the Navier--Stokes Equation in the Presence of Model Error (Q4627434) (← links)
- Learning interacting particle systems: Diffusion parameter estimation for aggregation equations (Q4630566) (← links)
- Efficient State/Parameter Estimation in Nonlinear Unsteady PDEs by a Reduced Basis Ensemble Kalman Filter (Q4636410) (← links)
- Minimax state estimates for abstract Neumann problems (Q4636816) (← links)
- Convergence analysis of ensemble Kalman inversion: the linear, noisy case (Q4638884) (← links)
- Uncertainty quantification and optimal decisions (Q4647203) (← links)
- A Fast Distributed Data-Assimilation Algorithm for Divergence-Free Advection (Q4685330) (← links)
- Flow state estimation in the presence of discretization errors (Q4961080) (← links)
- Affine Invariant Interacting Langevin Dynamics for Bayesian Inference (Q4964234) (← links)
- State estimation in turbulent channel flow from limited observations (Q4988005) (← links)
- Using data assimilation to train a hybrid forecast system that combines machine-learning and knowledge-based components (Q4993713) (← links)
