most citedGNN-Surrogate: A Hierarchical and Adaptive Graph Neural Network for Parameter Space Exploration of Unstructured-Mesh Ocean Simulations

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

physics.ao-ph2022★ 1 cited

GNN-Surrogate: A Hierarchical and Adaptive Graph Neural Network for Parameter Space Exploration of Unstructured-Mesh Ocean Simulations

Neng Shi, Jiayi Xu, Skylar W. Wurster +4

We propose GNN-Surrogate, a graph neural network-based surrogate model to explore the parameter space of ocean climate simulations. Parameter space exploration is important for dom…

cs.DC2019

The ISTI Rapid Response on Exploring Cloud Computing 2018

Carleton Coffrin, James Arnold, Stephan Eidenbenz +45

This report describes eighteen projects that explored how commercial cloud computing services can be utilized for scientific computation at national laboratories. These demonstrati…