Fast Learning Rates for Physics-Informed Kernel Methods
This work considers the setting where $D$ is a linear differential operator and analyzes a physics-informed kernel estimator combining value observations and differential observations to derive physically consistent rates in a stronger norm that jointly controls the errors in $\hat u$ and $D\hat u$.
Luc Brogat-Motte, Joachim Bona-Pellissier, Giacomo Meanti et al.
· 0 citations