Eric J. Parish
Eric J. Parish
Verified email at sandia.gov - Homepage
Title
Cited by
Cited by
Year
A paradigm for data-driven predictive modeling using field inversion and machine learning
EJ Parish, K Duraisamy
Journal of Computational Physics 305, 758-774, 2016
2922016
A priori estimation of memory effects in reduced-order models of nonlinear systems using the Mori–Zwanzig formalism
A Gouasmi, EJ Parish, K Duraisamy
Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2017
51*2017
Non-Markovian closure models for large eddy simulations using the Mori-Zwanzig formalism
EJ Parish, K Duraisamy
Phys. Rev. Fluids 2 (1), 014604, 2017
402017
A dynamic subgrid scale model for large eddy simulations based on the Mori–Zwanzig formalism
EJ Parish, K Duraisamy
Journal of Computational Physics 349, 154-175, 2017
392017
The Adjoint Petrov–Galerkin method for non-linear model reduction
EJ Parish, CR Wentland, K Duraisamy
Computer Methods in Applied Mechanics and Engineering 365, 112991, 2020
28*2020
Reduced order modeling of turbulent flows using statistical coarse-graining
E Parish, K Duraisamy
46th AIAA Fluid Dynamics Conference, 3640, 2016
132016
A unified framework for multiscale modeling using the mori-zwanzig formalism and the variational multiscale method
EJ Parish, K Duraisamy
arXiv preprint arXiv:1712.09669, 2017
122017
Time-series machine-learning error models for approximate solutions to parameterized dynamical systems
EJ Parish, KT Carlberg
Computer Methods in Applied Mechanics and Engineering 365, 112990, 2020
112020
Quantification of turbulence modeling uncertainties using full field inversion
E Parish, K Duraisamy
22nd AIAA Computational Fluid Dynamics Conference, 2459, 2015
102015
Generalized Riemann problem-based upwind scheme for the vorticity transport equations
E Parish, K Duraisamy, P Chandrashekar
Computers & Fluids 132, 10-18, 2016
82016
Windowed least-squares model reduction for dynamical systems
EJ Parish, KT Carlberg
Journal of Computational Physics 426, 109939, 2021
62021
Parameterized neural ordinary differential equations: Applications to computational physics problems
K Lee, EJ Parish
arXiv preprint arXiv:2010.14685, 2020
32020
Variational multiscale modeling and memory effects in turbulent flow simulations
E Parish
22018
Windowed space-time least-squares Petrov-Galerkin method for nonlinear model order reduction
YS Shimizu, EJ Parish
arXiv preprint arXiv:2012.06073, 2020
12020
Machine Learning Closure Modeling for Reduced-Order Models of Dynamical Systems.
EJ Parish
Sandia National Lab.(SNL-CA), Livermore, CA (United States), 2019
12019
A dynamic subgrid-scale model for LES based on the Mori-Zwanzig formalism
E Parish, K Duraisamy
Proceedings of the Summer Program, 275, 2016
12016
A compute-bound formulation of Galerkin model reduction for linear time-invariant dynamical systems
F Rizzi, EJ Parish, PJ Blonigan, J Tencer
Computer Methods in Applied Mechanics and Engineering 384, 113973, 2021
2021
Enabling efficient uncertainty quantification for seismic modeling via projection-based model reduction
F Rizzi, E Parish, P Blonigan, J Tencer
EGU General Assembly Conference Abstracts, EGU21-4807, 2021
2021
Model Reduction via Time-Continuous Least-Squares Residual Minimization
E Parish
APS Division of Fluid Dynamics Meeting Abstracts, L10. 002, 2019
2019
Time-series Machine Learning Error Models for Appproximate Solutions to Dynamical Systems.
EJ Parish, KT Carlberg
Sandia National Lab.(SNL-CA), Livermore, CA (United States), 2019
2019
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Articles 1–20