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cs.LG2025
A Low-complexity Structured Neural Network to Realize States of Dynamical Systems
Hansaka Aluvihare, Levi Lingsch, Xianqi Li +1
Data-driven learning is rapidly evolving and places a new perspective on realizing state-space dynamical systems. However, dynamical systems derived from nonlinear ordinary differe…
cs.LG2024
Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains
Levi Lingsch, Mike Y. Michelis, Emmanuel de Bezenac +3
The computational efficiency of many neural operators, widely used for learning solutions of PDEs, relies on the fast Fourier transform (FFT) for performing spectral computations.…