Random Feature Method (RFM) tools in Python
Project description
A Python package for Random Feature Method (RFM)
Quick Install
conda create -n pyRFM python=3.10 -y
conda activate pyRFM
pip install pyrfm
To get the source code and examples, you can clone the repository:
git clone https://github.com/IFaay/pyRFM.git
cd pyRFM
Update
pip install --upgrade --force-reinstall pyrfm
# git pull # Update local source
and re-download / pull the source code.
Remark
All examples run successfully on a host equipped with 8GB of GPU memory and 32GB of RAM. Example scripts are located in the examples folder.
Reference
[1] J. Chen, X. Chi, W. E, and Z. Yang, “Bridging traditional and machine learning-based algorithms for solving pdes: The random feature method,” J. Mach. Learn., vol. 1, no. 3, pp. 268–298, 2022, doi: 10.4208/jml.220726.
[2] J. Chen, W. E, and Y. Luo, “The random feature method for time-dependent problems,” East Asian Journal on Applied Mathematics, vol. 13, no. 3, pp. 435–463, 2023, doi: 10.4208/eajam.2023-065.050423.
[3] J. Chen, W. E, and Y. Sun, “Optimization of Random Feature Method in the High-Precision Regime,” Com Appl Math Comput, Mar. 2024, doi: 10.1007/s42967-024-00389-8.
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