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NeuralOperators.jl

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ColPrac: Contributor's Guide on Collaborative Practices for Community Packages SciML Code Style

NeuralOperators.jl is a package written in Julia to provide the architectures for learning mapping between function spaces, and learning grid invariant solution of PDEs. Checkout the documentation for tutorials and API reference.

Installation

On Julia 1.10+, you can install NeuralOperators.jl by running

import Pkg
Pkg.add("NeuralOperators")

Citation

If you found this library to be useful in academic work, then please cite:

@software{pal2023lux,
  author    = {Pal, Avik},
  title     = {{Lux: Explicit Parameterization of Deep Neural Networks in Julia}},
  month     = apr,
  year      = 2023,
  note      = {If you use this software, please cite it as below.},
  publisher = {Zenodo},
  version   = {v0.5.0},
  doi       = {10.5281/zenodo.7808904},
  url       = {https://doi.org/10.5281/zenodo.7808904}
}

@thesis{pal2023efficient,
  title     = {{On Efficient Training \& Inference of Neural Differential Equations}},
  author    = {Pal, Avik},
  year      = {2023},
  school    = {Massachusetts Institute of Technology}
}