GNN-Surrogate: A Hierarchical and Adaptive Graph Neural Network for Parameter Space Exploration of Unstructured-Mesh Ocean Simulations
IEEE Transactions on Visualization and Computer Graphics(2022)
摘要
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 domain scientists to understand the influence of input parameters (e.g., wind stress) on the simulation output (e.g., temperature). The exploration requires scientists to exhaust the complicated parameter space by running a...
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关键词
Computational modeling,Adaptation models,Predictive models,Data models,Space exploration,Analytical models,Data visualization
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