Bethany Lusch
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Citado por
Citado por
Año
Deep learning for universal linear embeddings of nonlinear dynamics
B Lusch, JN Kutz, SL Brunton
Nature communications 9 (1), 1-10, 2018
3382018
Data-driven discovery of coordinates and governing equations
K Champion, B Lusch, JN Kutz, SL Brunton
Proceedings of the National Academy of Sciences 116 (45), 22445-22451, 2019
1382019
Time-series learning of latent-space dynamics for reduced-order model closure
R Maulik, A Mohan, B Lusch, S Madireddy, P Balaprakash, D Livescu
Physica D: Nonlinear Phenomena 405, 132368, 2020
452020
Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders
R Maulik, B Lusch, P Balaprakash
Physics of Fluids 33 (3), 037106, 2021
312021
Inferring connectivity in networked dynamical systems: Challenges using Granger causality
B Lusch, PD Maia, JN Kutz
Physical Review E 94 (3), 032220, 2016
232016
Deep learning models for global coordinate transformations that linearise PDEs
C Gin, B Lusch, SL Brunton, JN Kutz
European Journal of Applied Mathematics 32 (3), 515-539, 2021
172021
Submodular hamming metrics
J Gillenwater, R Iyer, B Lusch, R Kidambi, J Bilmes
arXiv preprint arXiv:1511.02163, 2015
162015
Recurrent neural network architecture search for geophysical emulation
R Maulik, R Egele, B Lusch, P Balaprakash
arXiv preprint arXiv:2004.10928, 2020
152020
Accelerating RANS turbulence modeling using potential flow and machine learning
R Maulik, H Sharma, S Patel, B Lusch, E Jennings
arXiv preprint arXiv:1910.10878, 2019
122019
Modeling cognitive deficits following neurodegenerative diseases and traumatic brain injuries with deep convolutional neural networks
B Lusch, J Weholt, PD Maia, JN Kutz
Brain and cognition 123, 154-164, 2018
82018
Deep learning for universal linear embeddings of nonlinear dynamics Nat
B Lusch, JN Kutz, SL Brunton
Commun 9, 1-10, 2018
82018
A turbulent eddy-viscosity surrogate modeling framework for Reynolds-Averaged Navier-Stokes simulations
R Maulik, H Sharma, S Patel, B Lusch, E Jennings
Computers & Fluids, 104777, 2020
72020
Non-autoregressive time-series methods for stable parametric reduced-order models
R Maulik, B Lusch, P Balaprakash
Physics of Fluids 32 (8), 087115, 2020
72020
Mela: A visual analytics tool for studying multifidelity hpc system logs
FNU Shilpika, B Lusch, M Emani, V Vishwanath, ME Papka, KL Ma
2019 IEEE/ACM Industry/University Joint International Workshop on Data …, 2019
42019
Data-driven model reduction of multiphase flow in a single-hole automotive injector
PJ Milan, R Torelli, B Lusch, GM Magnotti
Atomization and Sprays 30 (6), 2020
32020
Deploying deep learning in OpenFOAM with TensorFlow
R Maulik, H Sharma, S Patel, B Lusch, E Jennings
AIAA Scitech 2021 Forum, 1485, 2021
22021
Accelerating RANS simulations using a data-driven framework for eddy-viscosity emulation
R Maulik, H Sharma, S Patel, B Lusch, E Jennings
arXiv preprint arXiv:1910.10878, 2019
22019
Using recurrent neural networks for nonlinear component computation in advection-dominated reduced-order models
R Maulik, V Rao, S Madireddy, B Lusch, P Balaprakash
arXiv preprint arXiv:1909.09144, 2019
22019
Shape Constrained Tensor Decompositions
B Lusch, EC Chi, JN Kutz
2019 IEEE International Conference on Data Science and Advanced Analytics …, 2019
12019
Shape constrained tensor decompositions using sparse representations in over-complete libraries
B Lusch, EC Chi, JN Kutz
arXiv preprint arXiv:1608.04674, 2016
12016
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20