Bethany Lusch

According to our database, Bethany Lusch authored at least 18 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling.

Shivam Barwey, Riccardo Balin, Bethany Lusch, Saumil Patel, Ramesh Balakrishnan, Pinaki Pal, Romit Maulik, Venkatram Vishwanath

CoRR, 2024

Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks.

Shivam Barwey, Pinaki Pal, Saumil Patel, Riccardo Balin, Bethany Lusch, Venkatram Vishwanath, Romit Maulik, Ramesh Balakrishnan

CoRR, 2024

A Multi-Level, Multi-Scale Visual Analytics Approach to Assessment of Multifidelity HPC Systems.

Shilpika, Bethany Lusch, Murali Emani, Filippo Simini, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma

Proceedings of the 24th IEEE International Symposium on Cluster, 2024

2023

Computationally Efficient Data-Driven Discovery and Linear Representation of Nonlinear Systems for Control.

Madhur Tiwari, George Nehma, Bethany Lusch

IEEE Control. Syst. Lett., 2023

2022

PythonFOAM: In-situ data analyses with OpenFOAM and Python.

Romit Maulik, Dimitrios Fytanidis, Bethany Lusch, Venkatram Vishwanath, Saumil Patel

J. Comput. Sci., 2022

AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification.

Romain Egele, Romit Maulik, Krishnan Raghavan, Bethany Lusch, Isabelle Guyon, Prasanna Balaprakash

Proceedings of the 26th International Conference on Pattern Recognition, 2022

Toward an In-Depth Analysis of Multifidelity High Performance Computing Systems.

Shilpika, Bethany Lusch, Murali Emani, Filippo Simini, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma

Proceedings of the 22nd IEEE International Symposium on Cluster, 2022

2021

AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification.

Romain Egele, Romit Maulik, Krishnan Raghavan, Prasanna Balaprakash, Bethany Lusch

CoRR, 2021

Data-Driven Deep Learning Emulators for Geophysical Forecasting.

Varuni Katti Sastry, Romit Maulik, Vishwas Rao, Bethany Lusch, S. Ashwin Renganathan, Rao Kotamarthi

Proceedings of the Computational Science - ICCS 2021, 2021

2020

Deploying deep learning in OpenFOAM with TensorFlow.

Romit Maulik, Himanshu Sharma, Saumil Patel, Bethany Lusch, Elise Jennings

CoRR, 2020

Recurrent neural network architecture search for geophysical emulation.

Romit Maulik, Romain Egele, Bethany Lusch, Prasanna Balaprakash

Proceedings of the International Conference for High Performance Computing, 2020

2019

Deep Learning Models for Global Coordinate Transformations that Linearize PDEs.

Craig Gin, Bethany Lusch, Steven L. Brunton, J. Nathan Kutz

CoRR, 2019

Using recurrent neural networks for nonlinear component computation in advection-dominated reduced-order models.

Romit Maulik, Vishwas Rao, Sandeep Madireddy, Bethany Lusch, Prasanna Balaprakash

CoRR, 2019

MELA: A Visual Analytics Tool for Studying Multifidelity HPC System Logs.

Shilpika, Bethany Lusch, Murali Emani, Venkatram Vishwanath, Michael E. Papka, Kwan-Liu Ma

Proceedings of the 3rd IEEE/ACM Industry/University Joint International Workshop on Data-center Automation, 2019

Shape Constrained Tensor Decompositions.

Bethany Lusch, Eric C. Chi, J. Nathan Kutz

Proceedings of the 2019 IEEE International Conference on Data Science and Advanced Analytics, 2019

2017

Deep learning for universal linear embeddings of nonlinear dynamics.

Bethany Lusch, J. Nathan Kutz, Steven L. Brunton

CoRR, 2017

2016

Shape Constrained Tensor Decompositions using Sparse Representations in Over-Complete Libraries.

Bethany Lusch, Eric C. Chi, J. Nathan Kutz

CoRR, 2016

2015

Submodular Hamming Metrics.

Jennifer Gillenwater, Rishabh K. Iyer, Bethany Lusch, Rahul Kidambi, Jeff A. Bilmes

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015