Optimal deep learning of holomorphic operators between Banach spaces Nick Dexter Department of Mathematics Department of Scientific Computing Simon Fraser University Florida State University Canada

Neural Information Processing Systems 

Operator learning problems arise in many key areas of scientific computing where Partial Differential Equations (PDEs) are used to model physical systems. In such scenarios, the operators map between Banach or Hilbert spaces. In this work, we tackle the problem of learning operators between Banach spaces, in contrast to the vast majority of past works considering only Hilbert spaces. We focus on learning holomorphic operators - an important class of problems with many applications.

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