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cs.LG2024
Scaling Continuous Kernels with Sparse Fourier Domain Learning
Clayton Harper, Luke Wood, Peter Gerstoft +1
We address three key challenges in learning continuous kernel representations: computational efficiency, parameter efficiency, and spectral bias. Continuous kernels have shown sign…
cs.LG2023
Deep Learning based Spatially Dependent Acoustical Properties Recovery
Ruixian Liu, Peter Gerstoft
The physics-informed neural network (PINN) is capable of recovering partial differential equation (PDE) coefficients that remain constant throughout the spatial domain directly fro…