Neural networks regress oversized subspaces for parametric problems using subspace-specific losses, with theory and experiments showing improved accuracy and smoother mappings.
Proper orthogonal decomposition: Theory and reduced-order modelling.Lecture Notes, University of Konstanz, 4(4):1–29, 2013
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Deep Learning for Subspace Regression
Neural networks regress oversized subspaces for parametric problems using subspace-specific losses, with theory and experiments showing improved accuracy and smoother mappings.