Showing 2026Show all
3 papers · 1 filter
cs.CE2026
Higher-Order Fourier Neural Operator: Explicit Mode Mixer for Nonlinear PDEs
Alex Colagrande, Paul Caillon, Eva Feillet +1
Neural operators provide deep neural networks for learning mappings between function spaces. Among them, the Fourier Neural Operator (FNO) is particularly effective: its spectral c…
cs.LG2026
Limits of Resolution Equivariance in Fourier Neural Operators
Alex Colagrande, Paul Caillon, Eva Feillet +1
Fourier Neural Operators are often assumed to generalize across spatial resolutions, enabling training on a coarse grid and deployment on a finer grid. We test this assumption by c…
cs.CL2026
Polynomial Mixing for Efficient Self-supervised Speech Encoders
Eva Feillet, Ryan Whetten, David Picard +1
State-of-the-art speech-to-text models typically employ Transformer-based encoders that model token dependencies via self-attention mechanisms. However, the quadratic complexity of…