AI RESEARCH
MTL-FNO: A Lightweight Multi-Task Fourier Neural Operator for Sparse Field Reconstruction
arXiv CS.LG
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ArXi:2605.26718v1 Announce Type: new Efficient onboard multi-field sparse reconstruction is essential for the autonomous operation of aerospace vehicles. While existing deep learning models exhibit promise for single-field reconstruction, deploying multiple independent models leads to prohibitive model size growth and fails to exploit cross-field correlations, particularly under few-shot conditions. To address these challenges, we first propose a lightweight multi-task Fourier neural operator (MTL-FNO), an end-to-end joint.