Bethany Lusch

Publication Activity (10 Years)

Years Active: 2015-2023
Publications (10 Years): 17

Top Topics

Nonlinear Dynamics

Top Venues

IEEE Control. Syst. Lett.

Publications

Madhur Tiwari, George Nehma, Bethany Lusch
Computationally Efficient Data-Driven Discovery and Linear Representation of Nonlinear Systems For Control. CoRR (2023)
Shilpika, Bethany Lusch, Murali Emani, Filippo Simini, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma
A Multi-Level, Multi-Scale Visual Analytics Approach to Assessment of Multifidelity HPC Systems. CoRR (2023)
Madhur Tiwari, George Nehma, Bethany Lusch
Computationally Efficient Data-Driven Discovery and Linear Representation of Nonlinear Systems for Control. IEEE Control. Syst. Lett. 7 (2023)
Romit Maulik, Dimitrios Fytanidis, Bethany Lusch, Venkatram Vishwanath, Saumil Patel
PythonFOAM: In-situ data analyses with OpenFOAM and Python. J. Comput. Sci. 62 (2022)
Romain Egele, Romit Maulik, Krishnan Raghavan, Bethany Lusch, Isabelle Guyon, Prasanna Balaprakash
AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification. ICPR (2022)
Shilpika, Bethany Lusch, Murali Emani, Filippo Simini, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma
Toward an In-Depth Analysis of Multifidelity High Performance Computing Systems. CCGRID (2022)
Romain Egele, Romit Maulik, Krishnan Raghavan, Prasanna Balaprakash, Bethany Lusch
AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification. CoRR (2021)
Romit Maulik, Dimitrios Fytanidis, Bethany Lusch, Venkatram Vishwanath, Saumil Patel
PythonFOAM: In-situ data analyses with OpenFOAM and Python. CoRR (2021)
Varuni Katti Sastry, Romit Maulik, Vishwas Rao, Bethany Lusch, S. Ashwin Renganathan, Rao Kotamarthi
Data-Driven Deep Learning Emulators for Geophysical Forecasting. ICCS (5) (2021)
Romit Maulik, Romain Egele, Bethany Lusch, Prasanna Balaprakash
Recurrent neural network architecture search for geophysical emulation. SC (2020)
Romit Maulik, Himanshu Sharma, Saumil Patel, Bethany Lusch, Elise Jennings
Deploying deep learning in OpenFOAM with TensorFlow. CoRR (2020)
Romit Maulik, Vishwas Rao, Sandeep Madireddy, Bethany Lusch, Prasanna Balaprakash
Using recurrent neural networks for nonlinear component computation in advection-dominated reduced-order models. CoRR (2019)
Bethany Lusch, Eric C. Chi, J. Nathan Kutz
Shape Constrained Tensor Decompositions. DSAA (2019)
Shilpika, Bethany Lusch, Murali Emani, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma
MELA: A Visual Analytics Tool for Studying Multifidelity HPC System Logs. DAAC@SC (2019)
Craig Gin, Bethany Lusch, Steven L. Brunton, J. Nathan Kutz
Deep Learning Models for Global Coordinate Transformations that Linearize PDEs. CoRR (2019)
Bethany Lusch, J. Nathan Kutz, Steven L. Brunton
Deep learning for universal linear embeddings of nonlinear dynamics. CoRR (2017)
Bethany Lusch, Eric C. Chi, J. Nathan Kutz
Shape Constrained Tensor Decompositions using Sparse Representations in Over-Complete Libraries. CoRR (2016)
Jennifer Gillenwater, Rishabh K. Iyer, Bethany Lusch, Rahul Kidambi, Jeff A. Bilmes
Submodular Hamming Metrics. NIPS (2015)
Jennifer Gillenwater, Rishabh K. Iyer, Bethany Lusch, Rahul Kidambi, Jeff A. Bilmes
Submodular Hamming Metrics. CoRR (2015)