CNNs achieve simultaneous Sobolev approximation on manifolds with intrinsic-dimension rates and enable a PICNN for BVPs via spectral boundary loss that improves stability over standard PINNs.
A novel Galerkin method for solving PDEs on the sphere using highly localized kernel bases.Mathematics of Computation, 86(303):197–231, 2017
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Simultaneous CNN Approximation on Manifolds with Applications to Boundary Value Problems
CNNs achieve simultaneous Sobolev approximation on manifolds with intrinsic-dimension rates and enable a PICNN for BVPs via spectral boundary loss that improves stability over standard PINNs.