To solve PDEs, you can learn at a fixed resolution (e.g. with U-net) and interpolate. But error cannot be arbitrarily small this way. Our neural operators are guaranteed to approximate arbitrarily well at any resolution since they learn in function space https://
arxiv.org/abs/2108.08481
Neural Operators for PDEs: Resolution-Independent Function Space Learning
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