PROSE: Predicting Multiple Operators and Symbolic Expressions

This repository contains code for the following papers:

• PROSE: Predicting Multiple Operators and Symbolic Expressions using Multimodal Transformers. More details can be found in prose_ode/README.md.

• Towards a Foundation Model for Partial Differential Equations: Multi-Operator Learning and Extrapolation. More details can be found in prose_pde/README.md.

• PROSE-FD: A Multimodal PDE Foundation Model for Learning Multiple Operators for Forecasting Fluid Dynamics. More details can be found in prose_fd/README.md.

Install dependencies

Using conda and the env.yml file:

conda env create --name prose --file=env.yml

Citation

If you find our paper and code useful, please consider citing:

@article{liu2024prose,
  title={{PROSE}: Predicting multiple operators and symbolic expressions using multimodal transformers},
  author={Liu, Yuxuan and Zhang, Zecheng and Schaeffer, Hayden},
  journal={Neural Networks},
  pages={106707},
  year={2024},
  publisher={Elsevier}
}

@article{sun2024foundation,
  title={Towards a Foundation Model for Partial Differential Equations: Multi-Operator Learning and Extrapolation}, 
  author={Sun, Jingmin and Liu, Yuxuan and Zhang, Zecheng and Schaeffer, Hayden},
  journal={arXiv preprint arXiv:2404.12355},
  year={2024}
}

@article{liu2024prose_fd,
  title={{PROSE-FD}: A Multimodal PDE Foundation Model for Learning Multiple Operators for Forecasting Fluid Dynamics},
  author={Liu, Yuxuan and Sun, Jingmin and He, Xinjie and Pinney, Griffin and Zhang, Zecheng and Schaeffer, Hayden},
  journal={arXiv preprint arXiv:2409.09811},
  year={2024}
}