Eric J. Parish

16 papers Journal 16
YearRankTypeTitle / Venue / Authors
2026 J jnl
NN-OpInf: an operator inference approach using structure-preserving composable neural networks.
CoRR
Eric J. Parish, Anthony Gruber, Patrick J. Blonigan, Irina Tezaur
2025 J jnl
Hybrid coupling with operator inference and the overlapping Schwarz alternating method.
CoRR
Irina Tezaur, Eric J. Parish, Anthony Gruber, Ian Moore, Christopher R. Wentland, Alejandro Mota
2025 J jnl
Transmission Conditions for the Non-Overlapping Schwarz Coupling of Full Order and Operator Inference Models.
CoRR
Cameron Rodriguez, Irina Tezaur, Alejandro Mota, Anthony Gruber, Eric J. Parish, Christopher R. Wentland
2023 J jnl
Hyper-Reduced Autoencoders for Efficient and Accurate Nonlinear Model Reductions.
CoRR
Jorio Cocola, John Tencer, Francesco Rizzi, Eric J. Parish, Patrick J. Blonigan
2023 J jnl
On the impact of dimensionally-consistent and physics-based inner products for POD-Galerkin and least-squares model reduction of compressible flows.
J. Comput. Phys.
Eric J. Parish, Francesco Rizzi
2023 J jnl
Residual-based stabilized reduced-order models of the transient convection-diffusion-reaction equation obtained through discrete and continuous projection.
CoRR
Eric J. Parish, Masayuki Yano, Irina Tezaur, Traian Iliescu
2022 J jnl
On the impact of dimensionally-consistent and physics-based inner products for POD-Galerkin and least-squares model reduction of compressible flows.
CoRR
Eric J. Parish, Francesco Rizzi
2021 J jnl
Space-time reduced-order modeling for uncertainty quantification.
CoRR
Ruhui Jin, Francesco Rizzi, Eric J. Parish
2021 J jnl
Windowed least-squares model reduction for dynamical systems.
J. Comput. Phys.
Eric J. Parish, Kevin T. Carlberg
2020 J jnl
A compute-bound formulation of Galerkin model reduction for linear time-invariant dynamical systems.
CoRR
Francesco Rizzi, Eric J. Parish, Patrick J. Blonigan, John Tencer
2020 J jnl
Parameterized Neural Ordinary Differential Equations: Applications to Computational Physics Problems.
CoRR
Kookjin Lee, Eric J. Parish
2020 J jnl
Windowed space-time least-squares Petrov-Galerkin method for nonlinear model order reduction.
CoRR
Yukiko S. Shimizu, Eric J. Parish
2019 J jnl
Time-series machine-learning error models for approximate solutions to parameterized dynamical systems.
CoRR
Eric J. Parish, Kevin T. Carlberg
2019 J jnl
Windowed least-squares model reduction for dynamical systems.
CoRR
Eric J. Parish, Kevin T. Carlberg
2017 J jnl
A dynamic subgrid scale model for Large Eddy Simulations based on the Mori-Zwanzig formalism.
J. Comput. Phys.
Eric J. Parish, Karthik Duraisamy
2016 J jnl
A paradigm for data-driven predictive modeling using field inversion and machine learning.
J. Comput. Phys.
Eric J. Parish, Karthik Duraisamy