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A repository analyzing the impact of open-source code in machine learning, robotics, and controls research

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code-release

This repository contains all the data and plotting scripts required to reproduce the plots in our paper "What is the Impact of Releasing Code with Publications? Statistics from the Machine Learning, Robotics, and Control Communities." The preprint is available here.

Installation

Install/upgrade Python3 dependencies:

pip3 install --upgrade pip
pip3 install pyyaml
pip3 install tikzplotlib
pip3 install matplotlib --upgrade

This was tested on macOS 13.3 with the following:

anaconda                  2022.10  
matplotlib                3.7.1
pip                       23.0.1
python                    3.9.13 
pyyaml                    6.0
tikzplotlib               0.10.1

Use

Clone this repository and run its main.py script:

git clone https://github.com/utiasDSL/code-release.git
cd code-release/
python3 main.py

Output

The script will sequentially generate the following figures:

fig1 fig2

fig3 fig4

fig5 fig6

fig7

Contribution

Our determination of available open-source code for publications is not perfect. If we incorrectly associated your publication with or without code, please open a pull request with the correction. We appreciate your contributions!

Citation

Please cite our work (paper) or (preprint) as:

@ARTICLE{oscrelease2024,
      author={Zhou, Siqi and Brunke, Lukas and Tao, Allen and Hall, Adam W. and Bejarano, Federico Pizarro and Panerati, Jacopo and Schoellig, Angela P.},
      journal={IEEE Control Systems Magazine}, 
      title={What Is the Impact of Releasing Code With Publications? Statistics from the Machine Learning, Robotics, and Control Communities}, 
      year={2024},
      volume={44},
      number={4},
      pages={38-46},
      doi={10.1109/MCS.2024.3402888}
}

Learning Systems and Robotics Lab at the Technical University of Munich (TUM) and the University of Toronto

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A repository analyzing the impact of open-source code in machine learning, robotics, and controls research

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