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ORCIDAndrey A. Popov
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Books and Theses
- 2022
[b1]Andrey A. Popov:
Combining Data-driven and Theory-guided Models in Ensemble Data Assimilation. Virginia Tech, Blacksburg, VA, USA, 2022
Journal Articles
- 2025
- [j9]Amit N. Subrahmanya, Andrey A. Popov, Adrian Sandu:
Ensemble variational Fokker-Planck methods for data assimilation. J. Comput. Phys. 523: 113681 (2025) - [j8]Felipe Giraldo-Grueso
, Andrey A. Popov, Renato Zanetti:
Gaussian Mixture-Based Point Mass Filtering With Applications to Terrain-Relative Navigation. IEEE Trans. Aerosp. Electron. Syst. 61(3): 7062-7075 (2025) - [j7]Dalton Durant, Andrey A. Popov, Renato Zanetti:
Updating Gaussian Mixture Weights Using Posterior Estimates. IEEE Trans. Aerosp. Electron. Syst. 61(4): 9392-9405 (2025) - 2024
- [j6]Yuqin Jiang, Andrey A. Popov, Zhenlong Li, Michael E. Hodgson, Binghu Huang:
A Sensor-Based Simulation Method for Spatiotemporal Event Detection. ISPRS Int. J. Geo Inf. 13(5): 141 (2024) - [j5]Felipe Giraldo-Grueso, Andrey A. Popov, Renato Zanetti:
Precision Mars Entry Navigation with Atmospheric Density Adaptation via Neural Networks. J. Aerosp. Inf. Syst. 21(12): 982-995 (2024) - [j4]Andrey A. Popov, Renato Zanetti:
An Adaptive Covariance Parameterization Technique for the Ensemble Gaussian Mixture Filter. SIAM J. Sci. Comput. 46(3): 1949- (2024) - 2022
- [j3]Andrey A. Popov, Adrian Sandu:
Multifidelity Ensemble Kalman Filtering Using Surrogate Models Defined by Theory-Guided Autoencoders. Frontiers Appl. Math. Stat. 8: 904687 (2022) - [j2]Steven B. Roberts, Andrey A. Popov, Arash Sarshar, Adrian Sandu:
A Fast Time-Stepping Strategy for Dynamical Systems Equipped with a Surrogate Model. SIAM J. Sci. Comput. 44(3): 1405- (2022) - 2021
- [j1]Andrey A. Popov, Changhong Mou, Adrian Sandu, Traian Iliescu:
A Multifidelity Ensemble Kalman Filter with Reduced Order Control Variates. SIAM J. Sci. Comput. 43(2): A1134-A1162 (2021)
Conference and Workshop Papers
- 2024
- [c8]Dalton Durant, Andrey A. Popov, Renato Zanetti:
What are You Weighting For? Improved Weights for Gaussian Mixture Filtering. FUSION 2024: 1-8 - [c7]Felipe Giraldo-Grueso, Andrey A. Popov, Renato Zanetti:
Gaussian Mixture-Based Point Mass Filtering. FUSION 2024: 1-8 - [c6]Rachel Mamich, Kristen Michaelson, Andrey A. Popov, Renato Zanetti:
Burnished Flow Filter. FUSION 2024: 1-8 - [c5]Kristen Michaelson, Andrey A. Popov, Renato Zanetti, Kyle J. DeMars:
Particle Flow with a Continuous Formulation of the Nonlinear Measurement Update. FUSION 2024: 1-8 - [c4]Andrey A. Popov, Renato Zanetti:
Are Non-Gaussian Kernels Suitable for Ensemble Mixture Model Filtering? FUSION 2024: 1-8 - 2023
- [c3]Kristen Michaelson, Andrey A. Popov, Renato Zanetti:
Ensemble Kalman Filter with Bayesian Recursive Update. FUSION 2023: 1-6 - [c2]Andrey A. Popov, Renato Zanetti:
Ensemble Gaussian Mixture Filtering with Particle-localized Covariances. FUSION 2023: 1-7 - [c1]Benjamin L. Reifler, Andrey A. Popov, Brandon A. Jones, Renato Zanetti:
Large-Scale Space Object Tracking in a Proliferated LEO Scenario. FUSION 2023: 1-8
Informal and Other Publications
- 2025
- [i26]Yuqin Jiang, Andrey A. Popov, Tianle Duan, Qingchun Li:
Downscaling human mobility data based on demographic socioeconomic and commuting characteristics using interpretable machine learning methods. CoRR abs/2509.21703 (2025) - [i25]Jostein Barry-Straume, Adwait Verulkar, Arash Sarshar, Andrey A. Popov, Adrian Sandu:
Ensemble based Closed-Loop Optimal Control using Physics-Informed Neural Networks. CoRR abs/2510.18195 (2025) - 2024
- [i24]Felipe Giraldo-Grueso, Andrey A. Popov, Renato Zanetti:
Precision Mars Entry Navigation with Atmospheric Density Adaptation via Neural Networks. CoRR abs/2401.14411 (2024) - [i23]Abhinab Bhattacharjee, Andrey A. Popov, Arash Sarshar, Adrian Sandu:
Improving the Adaptive Moment Estimation (ADAM) stochastic optimizer through an Implicit-Explicit (IMEX) time-stepping approach. CoRR abs/2403.13704 (2024) - [i22]Amit N. Subrahmanya, Andrey A. Popov, Reid Gomillion, Adrian Sandu:
Preserving Nonlinear Constraints in Variational Flow Filtering Data Assimilation. CoRR abs/2405.04380 (2024) - [i21]Dalton Durant, Andrey A. Popov, Renato Zanetti:
What are You Weighting For? Improved Weights for Gaussian Mixture Filtering With Application to Cislunar Orbit Determination. CoRR abs/2405.11081 (2024) - [i20]Andrey A. Popov, Renato Zanetti:
The Ensemble Epanechnikov Mixture Filter. CoRR abs/2408.11164 (2024) - 2023
- [i19]Andrey A. Popov, Renato Zanetti:
Small-data Reduced Order Modeling of Chaotic Dynamics through SyCo-AE: Synthetically Constrained Autoencoders. CoRR abs/2305.08036 (2023) - [i18]Andrey A. Popov, Renato Zanetti:
Ensemble-localized Kernel Density Estimation with Applications to the Ensemble Gaussian Mixture Filter. CoRR abs/2308.14143 (2023) - [i17]Kristen Michaelson, Andrey A. Popov, Renato Zanetti:
Bayesian Recursive Update for Ensemble Kalman Filters. CoRR abs/2310.18442 (2023) - 2022
- [i16]Jostein Barry-Straume, Arash Sarshar, Andrey A. Popov, Adrian Sandu:
Physics-informed neural networks for PDE-constrained optimization and control. CoRR abs/2205.03377 (2022) - [i15]Andrey A. Popov, Arash Sarshar, Austin Chennault, Adrian Sandu:
A Meta-learning Formulation of the Autoencoder Problem for Non-linear Dimensionality Reduction. CoRR abs/2207.06676 (2022) - [i14]Yuqin Jiang, Andrey A. Popov, Zhenlong Li, Michael E. Hodgson:
An optimal sensors-based simulation method for spatiotemporal event detection. CoRR abs/2208.07969 (2022) - [i13]Andrey A. Popov, Adrian Sandu:
The Model Forest Ensemble Kalman Filter. CoRR abs/2210.11971 (2022) - [i12]Andrey A. Popov, Renato Zanetti:
An Adaptive Covariance Parameterization Technique for the Ensemble Gaussian Mixture Filter. CoRR abs/2212.10323 (2022) - 2021
- [i11]Andrey A. Popov, Adrian Sandu:
Multifidelity Ensemble Kalman Filtering using surrogate models defined by Physics-Informed Autoencoders. CoRR abs/2102.13025 (2021) - [i10]Rachel Cooper, Andrey A. Popov, Adrian Sandu:
Investigation of Nonlinear Model Order Reduction of the Quasigeostrophic Equations through a Physics-Informed Convolutional Autoencoder. CoRR abs/2108.12344 (2021) - [i9]Andrey A. Popov, Amit N. Subrahmanya, Adrian Sandu:
A Stochastic Covariance Shrinkage Approach to Particle Rejuvenation in the Ensemble Transform Particle Filter. CoRR abs/2109.09673 (2021) - [i8]Austin Chennault, Andrey A. Popov, Amit N. Subrahmanya, Rachel Cooper, Anuj Karpatne, Adrian Sandu:
Adjoint-Matching Neural Network Surrogates for Fast 4D-Var Data Assimilation. CoRR abs/2111.08626 (2021) - [i7]Amit N. Subrahmanya, Andrey A. Popov, Adrian Sandu:
An Ensemble Variational Fokker-Planck Method for Data Assimilation. CoRR abs/2111.13926 (2021) - 2020
- [i6]Andrey A. Popov, Adrian Sandu, Elias David Niño Ruiz, Geir Evensen:
A Stochastic Covariance Shrinkage Approach in Ensemble Transform Kalman Filtering. CoRR abs/2003.00354 (2020) - [i5]Andrey A. Popov, Adrian Sandu:
An Explicit Probabilistic Derivation of Inflation in a Scalar Ensemble Kalman Filter for Finite Step, Finite Ensemble Convergence. CoRR abs/2003.13162 (2020) - [i4]Andrey A. Popov, Changhong Mou, Traian Iliescu, Adrian Sandu:
A Multifidelity Ensemble Kalman Filter with Reduced Order Control Variates. CoRR abs/2007.00793 (2020) - [i3]Steven B. Roberts, Andrey A. Popov, Arash Sarshar, Adrian Sandu:
A fast time-stepping strategy for ODE systems equipped with a surrogate model. CoRR abs/2011.03688 (2020) - 2019
- [i2]Steven B. Roberts, Andrey A. Popov, Adrian Sandu:
ODE Test Problems: a MATLAB suite of initial value problems. CoRR abs/1901.04098 (2019) - 2018
- [i1]Andrey A. Popov, Adrian Sandu:
A Bayesian Approach to Multivariate Adaptive Localization in Ensemble-Based Data Assimilation with Time-Dependent Extensions. CoRR abs/1809.08984 (2018)
Coauthor Index
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