An iterative PCA plus curve-unfolding method splits a parameter domain into subdomains, enabling local ML models that outperform a global model on a test PDE problem.
A training set and multiple bases generation approach for parameterized model reduction based on adaptive grids in parameter space
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A new methodology to decompose a parametric domain using reduced order data manifold in machine learning
An iterative PCA plus curve-unfolding method splits a parameter domain into subdomains, enabling local ML models that outperform a global model on a test PDE problem.