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Articles by Adrian Sandu

Improving the Adaptive Moment Estimation (ADAM) stochastic optimizer through an Implicit-Explicit (IMEX) time-stepping approach
14 September 2024 by Abhinab Bhattacharjee and others
Computational Engineering, Finance, and Science, Machine Learning
Preserving Nonlinear Constraints in Variational Flow Filtering Data Assimilation
7 May 2024 by Amit Subrahmanya and others
Optimization and Control, Computational Engineering, Finance, and Science
Ensemble Variational Fokker-Planck Methods for Data Assimilation
19 January 2024 by Amit Subrahmanya and others at LogoVirginia Tech
Optimization and Control, Computational Engineering, Finance, and Science
Simultaneous Optimal System and Controller Design for Multibody Systems with Joint Friction using Direct Sensitivities
25 December 2023 by Adwait Verulkar and others
Systems and Control, Computational Engineering, Finance, and Science
Symplectic multirate generalized additive Runge-Kutta methods for Hamiltonian systems
14 December 2023 by Kevin Schäfers and others
Numerical Analysis
Symplectic GARK methods for partitioned Hamiltonian systems
1
13 December 2023 by Michael Günther and others at LogoBergische Universität Gesamthochschule Wuppertal
Numerical Analysis
Adversarial Training Using Feedback Loops
24 August 2023 by Ali Haisam Muhammad Rafid and Adrian Sandu
Machine Learning, Cryptography and Security
Neural Network Reduction with Guided Regularizers
29 May 2023 by Ali Haisam Muhammad Rafid and Adrian Sandu
Machine Learning
Adjoint-Matching Neural Network Surrogates for Fast 4D-Var Data Assimilation
20 December 2022 by Austin Chennault and others
Machine Learning, Computational Engineering, Finance, and Science
A Two-Level Galerkin Reduced Order Model for the Steady Navier-Stokes Equations
23 November 2022 by Dylan Park and others
Numerical Analysis
The Model Forest Ensemble Kalman Filter
21 October 2022 by Andrey Popov and Adrian Sandu
Computational Engineering, Finance, and Science, Optimization and Control
Physics-informed neural networks for PDE-constrained optimization and control
18 August 2022 by Jostein Barry-Straume and others
Machine Learning, Optimization and Control
A Meta-learning Formulation of the Autoencoder Problem for Non-linear Dimensionality Reduction
27 July 2022 by Andrey Popov and others at LogoVirginia Tech
Machine Learning
Eliminating Order Reduction on Linear, Time-Dependent ODEs with GARK Methods
14 February 2022 by Steven Roberts and Adrian Sandu
Numerical Analysis
A Stochastic Covariance Shrinkage Approach to Particle Rejuvenation in the Ensemble Transform Particle Filter
20 September 2021 by Andrey Popov and others
Statistics Theory, Numerical Analysis
Multifidelity Ensemble Kalman Filtering Using Surrogate Models Defined by Physics-Informed Autoencoders
10 March 2021 by Andrey Popov and Adrian Sandu
Optimization and Control, Machine Learning
A unified formulation of splitting-based implicit time integration schemes
3 March 2021 by Severiano González-Pinto and others
Numerical Analysis
Multirate Linearly-Implicit GARK Schemes
19 February 2021 by Michael Guenther and Adrian Sandu
Numerical Analysis
A fast time-stepping strategy for dynamical systems equipped with a surrogate model
15 December 2020 by Steven Roberts and others
Numerical Analysis
Linearly Implicit Multistep Methods for Time Integration
21 November 2020 by Ross Glandon and others
Numerical Analysis
Linearly implicit GARK schemes
11 October 2020 by Adrian Sandu and others
Numerical Analysis
A Multifidelity Ensemble Kalman Filter with Reduced Order Control Variates
1 July 2020 by Andrey Popov and others
Numerical Analysis, Optimization and Control
Implicit multirate GARK methods
22 June 2020 by Steven Roberts and others
Numerical Analysis
Parallel implicit-explicit general linear methods
21 April 2020 by Steven Roberts and others
Numerical Analysis
Convergence Results for Implicit--Explicit General Linear Methods
8 April 2020 by Adrian Sandu
Numerical Analysis
An Explicit Probabilistic Derivation of Inflation in a Scalar Ensemble Kalman Filter for Finite Step, Finite Ensemble Convergence
29 March 2020 by Andrey Popov and Adrian Sandu
Optimization and Control, Numerical Analysis
A Stochastic Covariance Shrinkage Approach in Ensemble Transform Kalman Filtering
5 March 2020 by Andrey Popov and others
Methodology, Numerical Analysis
Goal-oriented a posteriori estimation of numerical errors in the solution of multiphysics systems
23 January 2020 by Mahesh Narayanamurthi and others
Numerical Analysis
Efficient implementation of partitioned stiff exponential Runge-Kutta methods
2 December 2019 by Mahesh Narayanamurthi and Adrian Sandu
Numerical Analysis
Adaptive Krylov-Type Time Integration Methods
6 October 2019 by Paul Tranquilli and others
Numerical Analysis
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