A Bayesian Approach to Multivariate Adaptive Localization in Ensemble-Based Data Assimilation with Time-Dependent Extensions. - Andrey A. Popov; Adrian Sandu (CoRR, 2018)

ODE Test Problems: a MATLAB suite of initial value problems. - Steven B. Roberts; Andrey A. Popov; Adrian Sandu (CoRR, 2019)

A Stochastic Covariance Shrinkage Approach in Ensemble Transform Kalman Filtering. - Andrey A. Popov; Adrian Sandu; Elias David Niño Ruiz; Geir Evensen (CoRR, 2020)

An Explicit Probabilistic Derivation of Inflation in a Scalar Ensemble Kalman Filter for Finite Step, Finite Ensemble Convergence. - Andrey A. Popov; Adrian Sandu (CoRR, 2020)

A fast time-stepping strategy for ODE systems equipped with a surrogate model. - Steven B. Roberts; Andrey A. Popov; Arash Sarshar; Adrian Sandu (CoRR, 2020)

Multifidelity Ensemble Kalman Filtering using surrogate models defined by Physics-Informed Autoencoders. - Andrey A. Popov; Adrian Sandu (CoRR, 2021)

Investigation of Nonlinear Model Order Reduction of the Quasigeostrophic Equations through a Physics-Informed Convolutional Autoencoder. - Rachel Cooper; Andrey A. Popov; Adrian Sandu (CoRR, 2021)

A Stochastic Covariance Shrinkage Approach to Particle Rejuvenation in the Ensemble Transform Particle Filter. - Andrey A. Popov; Amit N. Subrahmanya; Adrian Sandu (CoRR, 2021)

Adjoint-Matching Neural Network Surrogates for Fast 4D-Var Data Assimilation. - Austin Chennault; Andrey A. Popov; Amit N. Subrahmanya; Rachel Cooper; Anuj Karpatne; Adrian Sandu (CoRR, 2021)

An Ensemble Variational Fokker-Planck Method for Data Assimilation. - Amit N. Subrahmanya; Andrey A. Popov; Adrian Sandu (CoRR, 2021)

A Multifidelity Ensemble Kalman Filter with Reduced Order Control Variates. - Andrey A. Popov; Changhong Mou; Adrian Sandu; Traian Iliescu (SIAM J. Sci. Comput., 2021)

Physics-informed neural networks for PDE-constrained optimization and control. - Jostein Barry-Straume; Arash Sarshar; Andrey A. Popov; Adrian Sandu (CoRR, 2022)

A Meta-learning Formulation of the Autoencoder Problem for Non-linear Dimensionality Reduction. - Andrey A. Popov; Arash Sarshar; Austin Chennault; Adrian Sandu (CoRR, 2022)

An optimal sensors-based simulation method for spatiotemporal event detection. - Yuqin Jiang; Andrey A. Popov; Zhenlong Li; Michael E. Hodgson (CoRR, 2022)

The Model Forest Ensemble Kalman Filter. - Andrey A. Popov; Adrian Sandu (CoRR, 2022)

Multifidelity Ensemble Kalman Filtering Using Surrogate Models Defined by Theory-Guided Autoencoders. - Andrey A. Popov; Adrian Sandu (Frontiers Appl. Math. Stat., 2022)

A Fast Time-Stepping Strategy for Dynamical Systems Equipped with a Surrogate Model. - Steven B. Roberts; Andrey A. Popov; Arash Sarshar; Adrian Sandu (SIAM J. Sci. Comput., 2022)

Combining Data-driven and Theory-guided Models in Ensemble Data Assimilation. - Andrey A. Popov (2022)

Ensemble Kalman Filter with Bayesian Recursive Update. - Kristen Michaelson; Andrey A. Popov; Renato Zanetti (FUSION, 2023)

Ensemble Gaussian Mixture Filtering with Particle-localized Covariances. - Andrey A. Popov; Renato Zanetti (FUSION, 2023)

Large-Scale Space Object Tracking in a Proliferated LEO Scenario. - Benjamin L. Reifler; Andrey A. Popov; Brandon A. Jones; Renato Zanetti (FUSION, 2023)

Small-data Reduced Order Modeling of Chaotic Dynamics through SyCo-AE: Synthetically Constrained Autoencoders. - Andrey A. Popov; Renato Zanetti (CoRR, 2023)

Ensemble-localized Kernel Density Estimation with Applications to the Ensemble Gaussian Mixture Filter. - Andrey A. Popov; Renato Zanetti (CoRR, 2023)

Bayesian Recursive Update for Ensemble Kalman Filters. - Kristen Michaelson; Andrey A. Popov; Renato Zanetti (CoRR, 2023)

What are You Weighting For? Improved Weights for Gaussian Mixture Filtering. - Dalton Durant; Andrey A. Popov; Renato Zanetti (FUSION, 2024)

Gaussian Mixture-Based Point Mass Filtering. - Felipe Giraldo-Grueso; Andrey A. Popov; Renato Zanetti (FUSION, 2024)

Burnished Flow Filter. - Rachel Mamich; Kristen Michaelson; Andrey A. Popov; Renato Zanetti (FUSION, 2024)

Particle Flow with a Continuous Formulation of the Nonlinear Measurement Update. - Kristen Michaelson; Andrey A. Popov; Renato Zanetti; Kyle J. DeMars (FUSION, 2024)

Are Non-Gaussian Kernels Suitable for Ensemble Mixture Model Filtering? - Andrey A. Popov; Renato Zanetti (FUSION, 2024)

Improving the Adaptive Moment Estimation (ADAM) stochastic optimizer through an Implicit-Explicit (IMEX) time-stepping approach. - Abhinab Bhattacharjee; Andrey A. Popov; Arash Sarshar; Adrian Sandu (CoRR, 2024)

Preserving Nonlinear Constraints in Variational Flow Filtering Data Assimilation. - Amit N. Subrahmanya; Andrey A. Popov; Reid Gomillion; Adrian Sandu (CoRR, 2024)

What are You Weighting For? Improved Weights for Gaussian Mixture Filtering With Application to Cislunar Orbit Determination. - Dalton Durant; Andrey A. Popov; Renato Zanetti (CoRR, 2024)

The Ensemble Epanechnikov Mixture Filter. - Andrey A. Popov; Renato Zanetti (CoRR, 2024)

A Sensor-Based Simulation Method for Spatiotemporal Event Detection. - Yuqin Jiang; Andrey A. Popov; Zhenlong Li; Michael E. Hodgson; Binghu Huang (ISPRS Int. J. Geo Inf., 2024)

Precision Mars Entry Navigation with Atmospheric Density Adaptation via Neural Networks. - Felipe Giraldo-Grueso; Andrey A. Popov; Renato Zanetti (J. Aerosp. Inf. Syst., 2024)

An Adaptive Covariance Parameterization Technique for the Ensemble Gaussian Mixture Filter. - Andrey A. Popov; Renato Zanetti (SIAM J. Sci. Comput., 2024)

Ensemble variational Fokker-Planck methods for data assimilation. - Amit N. Subrahmanya; Andrey A. Popov; Adrian Sandu (J. Comput. Phys., 2025)

Gaussian Mixture-Based Point Mass Filtering With Applications to Terrain-Relative Navigation. - Felipe Giraldo-Grueso; Andrey A. Popov; Renato Zanetti (IEEE Trans. Aerosp. Electron. Syst., 2025)

Updating Gaussian Mixture Weights Using Posterior Estimates. - Dalton Durant; Andrey A. Popov; Renato Zanetti (IEEE Trans. Aerosp. Electron. Syst., 2025)