A constrained XGBoost framework maps Grassmann manifold subspaces to Euclidean space to predict parameter-dependent POD bases for adaptive reduced-order models in fluid and wave problems.
Adapting Projection-Based Reduced-Order Models using Projected Gaussian Process
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Constrained Extreme Gradient Boosting for Adapting Reduced-Order Models
A constrained XGBoost framework maps Grassmann manifold subspaces to Euclidean space to predict parameter-dependent POD bases for adaptive reduced-order models in fluid and wave problems.