| Deep convolutional recurrent autoencoders for learning low-dimensional feature dynamics of fluid systems FJ Gonzalez, M Balajewicz arXiv preprint arXiv:1808.01346, 2018 | 214 | 2018 |
| Low-dimensional modelling of high-Reynolds-number shear flows incorporating constraints from the Navier–Stokes equation M Balajewicz, E Dowell, B Noack Journal of Fluid Mechanics 729, 285-308, 2013 | 212 | 2013 |
| Reduced-order modeling of flutter and limit-cycle oscillations using the sparse Volterra series M Balajewicz, E Dowell Journal of Aircraft 49 (6), 1803-1812, 2012 | 126* | 2012 |
| Transported snapshot model order reduction approach for parametric, steady‐state fluid flows containing parameter‐dependent shocks NJ Nair, M Balajewicz International Journal for Numerical Methods in Engineering 117 (12), 1234-1262, 2019 | 105 | 2019 |
| Minimal subspace rotation on the Stiefel manifold for stabilization and enhancement of projection-based reduced order models for the compressible Navier-Stokes equations M Balajewicz, I Tezaur, E Dowell Journal of Computational Physics 321, 224-241, 2016 | 100 | 2016 |
| Projection‐based model reduction for contact problems M Balajewicz, D Amsallem, C Farhat International Journal for Numerical Methods in Engineering 106 (8), 644-663, 2016 | 98 | 2016 |
| Identification strategies for model-based control L Cordier, BR Noack, G Tissot, G Lehnasch, J Delville, M Balajewicz, ... Experiments in fluids 54, 1-21, 2013 | 98 | 2013 |
| Application of multi-input Volterra theory to nonlinear multi-degree-of-freedom aerodynamic systems M Balajewicz, F Nitzsche, D Feszty AIAA Journal 48 (1), 56-62, 2010 | 84 | 2010 |
| Stabilization of projection-based reduced order models of the Navier–Stokes equations M Balajewicz, E Dowell Nonlinear Dynamics 70 (2), 1619-1632, 2012 | 79 | 2012 |
| Lagrangian basis method for dimensionality reduction of convection dominated nonlinear flows R Mojgani, M Balajewicz arXiv preprint arXiv:1701.04343, 2017 | 68 | 2017 |
| Kolmogorov n–width and Lagrangian physics-informed neural networks: A causality-conforming manifold for convection-dominated PDEs R Mojgani, M Balajewicz, P Hassanzadeh Computer Methods in Applied Mechanics and Engineering 404, 115810, 2023 | 46 | 2023 |
| Reduced order models for pricing European and American options under stochastic volatility and jump-diffusion models M Balajewicz, J Toivanen Journal of Computational Science 20, 198-204, 2017 | 39* | 2017 |
| Reduction of nonlinear embedded boundary models for problems with evolving interfaces M Balajewicz, F Charbel Journal of Computational Physics 274, 489 - 504, 2014 | 39 | 2014 |
| Physics-aware registration based auto-encoder for convection dominated PDEs R Mojgani, M Balajewicz arXiv preprint arXiv:2006.15655, 2020 | 29 | 2020 |
| Reduced Order Models for Pricing European and American Options under Stochastic Volatility and Jump-Diffusion Models M Balajewicz, J Toivanen https://arxiv.org/abs/1612.00402, 2016 | 27 | 2016 |
| Lagrangian pinns: A causality-conforming solution to failure modes of physics-informed neural networks R Mojgani, M Balajewicz, P Hassanzadeh arXiv preprint arXiv:2205.02902, 2022 | 24 | 2022 |
| Low-rank registration based manifolds for convection-dominated PDEs R Mojgani, M Balajewicz Proceedings of the AAAI Conference on Artificial Intelligence 35 (1), 399-407, 2021 | 18 | 2021 |
| A study of the regularized lid-driven cavity’s progression to chaos MW Lee, EH Dowell, MJ Balajewicz Communications in Nonlinear Science and Numerical Simulation 71, 50-72, 2019 | 18 | 2019 |
| Learning low-dimensional feature dynamics using deep convolutional recurrent autoencoders FJ Gonzalez, M Balajewicz arXiv preprint arXiv:1808.01346, 2018 | 18 | 2018 |
| Arbitrary Lagrangian Eulerian framework for efficient projection-based reduction of convection dominated nonlinear flows R Mojgani, M Balajewicz APS Division of Fluid Dynamics Meeting Abstracts, M1. 008, 2017 | 17 | 2017 |
earl dowellПотвърден имейл адрес: duke.edu
