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.
On the rates of convergence for learning with convolutional neural networks.SIAM Journal on Mathematics of Data Science, 7 (4):1755–1772, 2025
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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.