Fares Mehouachi

Fractional is Better: Learnable Derivative Orders in Neural Operator Learning

Neural operators learn mappings between function spaces, enabling fast PDE surrogates. Despite architectural diversity, these methods often share a common input representation: raw coordinate-value pairs. This ignores the differential structure that defines the underlying physics. We study whether d…