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Code for the paper "The Random Feature Model for Input-Output Maps between Banach Spaces"

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random-features-banach

This repository contains the code associated with the journal articles "The Random Feature Model for Input-Output Maps between Banach Spaces" (SIAM J. Sci. Comput., 43 (2021), pp. A3212–A3243) and "Operator learning using random features: a tool for scientific computing" (to appear in SIAM Review, 2024). It implements the function-valued random features method for two operator learning benchmark problems: 1) the solution operator of 1D viscous Burgers' equation and 2) the solution operator of the 2D Darcy flow elliptic partial differential equation.

Important

A more efficient and up-to-date GPU implementation of this code is available at:

https://github.com/nickhnelsen/error-bounds-for-vvRF

We recommend that users interested in the operator random features method migrate over to that repository. The current repo random-features-banach should only be used to reproduce the results in the journal papers and not used for future developements.

Requirements

  • Python 3
  • Numpy
  • Numba
  • Scipy
  • Matplotlib

Data

The data may be downloaded at DOI, which contains two *.zip files:

  1. burgers: input-output data as Python *.npy files.
  2. darcy: input-output data as MATLAB *.mat files.
Nelsen, N. H. & Stuart, A.M. (2024). Operator learning using random features: a tool for scientific computing [Data set]. CaltechDATA. https://doi.org/10.22002/55tdh-hda68. Mar. 15, 2024.

References

The main reference that explains the two benchmark problems is the paper ``The Random Feature Model for Input-Output Maps between Banach Spaces'' by Nicholas H. Nelsen and Andrew M. Stuart. Other relevant references include:

Citing

If you use random-features-banach in an academic paper, please cite the main reference ``The random feature model for input-output maps between Banach spaces'' as follows:

@article{nelsen2021random,
  title={The random feature model for input-output maps between Banach spaces},
  author={Nelsen, Nicholas H and Stuart, Andrew M},
  journal={SIAM Journal on Scientific Computing},
  volume={43},
  number={5},
  pages={A3212--A3243},
  year={2021},
  publisher={Society for Industrial and Applied Mathematics}
}