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Operators can be learned more efficiently with kernel methods that outperform deep learning models while maintaining high predictive accuracy.
Multi-task operator learning with shared representations doesn't cost you extra – it scales just as well as learning each operator individually.
Achieve explicit generalization guarantees for Multiple Neural Operator (MNO) networks, revealing how performance scales with the number of sampled operators.
