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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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  • C++ 81.0%
  • Fortran 9.9%
  • C 3.0%
  • CMake 2.5%
  • Python 1.5%
  • Cuda 1.1%
  • Other 1.0%