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Python-C package for performing bayesian automated inference on data, based on probabilistic graphical models.

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gABi: graphical Automated Bayesian inference

Python package to perform Bayesian causal discovery on data, based on probabilistic graphical models.

This package has the following dependencies:

  • decorator
  • itertools (built-in)
  • matplotlib ( built-in
  • networkx (version > 2.6)
  • joblib
  • os
  • pandas
  • pypickle
  • scipy
  • statsmodels
  • tqdm
  • wget
  • pyarrow
  • Apache arrow
  • pybind11
  • dask
  • mpi4py

At the moment the gABI package provides the parallel version of the following structure learning algorithms:

  • PC-stable
  • kernel-PC

The algorithms depends on dask for the parallelization, and can be launched on CPUs and GPUs

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Python-C package for performing bayesian automated inference on data, based on probabilistic graphical models.

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