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Time-series learning of latent-space dynamics for reduced-order model closure

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ML_ROM_Closures

Time-series learning of latent-space dynamics for reduced-order model closure

R. Maulik, A. Mohan, B. Lusch, S. Madireddy, P. Balaprakash, D. Livescu

https://doi.org/10.1016/j.physd.2020.132368

Runs

These are results using the hand-tuned hyperparameters

HPS

These are results using deephyper for hyperparameter optimization

Note

For visualizing results from LSTM deployments use python Burgers_POD_ROM.py and for NODE deployments use python NODE_Burgers.py. Change deployment_mode = 'test' to deployment_mode = 'train' within these files to retrain the framework. This repo will have further documentation added to it slowly - in the meanwhile please contact rmaulik@anl.gov for any questions.

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Time-series learning of latent-space dynamics for reduced-order model closure

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