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20132023
most citedComparison of POD reduced order strategies for the nonlinear 2D Shallow Water Equations

108 citations · 525 across the 62 of their papers we have counts for

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Showing 2021Show all

8 papers · 1 filter

math.OC2021★ 4 cited

Ensemble Variational Fokker-Planck Methods for Data Assimilation

Amit N Subrahmanya, Andrey A Popov, Adrian Sandu

Particle flow filters solve Bayesian inference problems by smoothly transforming a set of particles into samples from the posterior distribution. Particles move in state space unde…

cs.LG2021

Adjoint-Matching Neural Network Surrogates for Fast 4D-Var Data Assimilation

Austin Chennault, Andrey A. Popov, Amit N. Subrahmanya +4

Data assimilation is the process of fusing information from imperfect computer simulations with noisy, sparse measurements of reality to obtain improved estimates of the state or p…

math.ST2021★ 4 cited

A Stochastic Covariance Shrinkage Approach to Particle Rejuvenation in the Ensemble Transform Particle Filter

Andrey A Popov, Amit N Subrahmanya, Adrian Sandu

Rejuvenation in particle filters is necessary to prevent the collapse of the weights when the number of particles is insufficient to sample the high probability regions of the stat…

cs.LG2021

Investigation of Nonlinear Model Order Reduction of the Quasigeostrophic Equations through a Physics-Informed Convolutional Autoencoder

Rachel Cooper, Andrey A. Popov, Adrian Sandu

Reduced order modeling (ROM) is a field of techniques that approximates complex physics-based models of real-world processes by inexpensive surrogates that capture important dynami…

math.OC2021★ 3 cited

Multifidelity Ensemble Kalman Filtering Using Surrogate Models Defined by Physics-Informed Autoencoders

Andrey A Popov, Adrian Sandu

Data assimilation is a Bayesian inference process that obtains an enhanced understanding of a physical system of interest by fusing information from an inexact physics-based model,…

math.NA2021★ 1 cited

Symplectic GARK methods for partitioned Hamiltonian systems

Michael Günther, Adrian Sandu, Kevin Schäfers +1

Generalized Additive Runge-Kutta schemes have shown to be a suitable tool for solving ordinary differential equations with additively partitioned right-hand sides. This work develo…

math.NA2021

A unified formulation of splitting-based implicit time integration schemes

Severiano González-Pinto, Domingo Hernández-Abreu, Maria S. Pérez-Rodríguez +3

Splitting-based time integration approaches such as fractional steps, alternating direction implicit, operator splitting, and locally one-dimensional methods partition the system o…

math.NA2021

Multirate Linearly-Implicit GARK Schemes

Michael Guenther, Adrian Sandu

Many complex applications require the solution of initial-value problems where some components change fast, while others vary slowly. Multirate schemes apply different step sizes t…