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Gradient-Based Neural DAG Learning

This code was written by the authors of the ICLR 2020 submission: "Gradient-Based Neural DAG Learning". Our implementation is in PyTorch but some functions rely on the Causal Discovery Toolbox which relies partly on the R programming language.

Run the code

To use our implementation of GraN-DAG, simply install Singularity (instructions: https://www.sylabs.io/guides/3.0/user-guide/installation.html) and run the code in our container (download it here: https://drive.google.com/file/d/1pcQB116Tt2IRoVPmqt610N0nPKUAwHsR/view?usp=sharing). Use start_example.sh (update the paths) to launch the differents methods (GraN-DAG, DAG-GNN, NOTEARS, CAM).

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  • Python 63.7%
  • Jupyter Notebook 19.6%
  • C++ 8.7%
  • R 7.5%
  • Shell 0.5%