Strudel -- Learning Structured-Decomposable Circuits

This repo contains the code and experiments from the paper "Strudel: Learning Structured-Decomposable Probabilistic Circuits", published in PGM 2020, and it's extended version "Strudel: A Fast and Accurate Learner of Structured-Decomposable Probabilistic Circuits", published in IJAR 2022.

To cite this paper, please use

@inproceedings{DangPGM20,
  author    = {Dang, Meihua and Vergari, Antonio and Van den Broeck, Guy},
  title     = {Strudel: Learning Structured-Decomposable Probabilistic Circuits},
  booktitle = {Proceedings of the 10th International Conference on Probabilistic Graphical Models (PGM)},
  month     = {sep},
  year      = {2020}}

or the extended version

@article{DangIJAR22,
    author = {Dang, Meihua and Vergari, Antonio and Van den Broeck, Guy},
    title = {Strudel: A Fast and Accurate Learner of Structured-Decomposable Probabilistic Circuits},
    journal = {International Journal of Approximate Reasoning},
    month = {Jan},
    year = {2022},
    volume = {140},
    pages = {92-115},
    issn = {0888-613X},
    doi = {https://doi.org/10.1016/j.ijar.2021.09.012}}

Files

bin/            Runnable julia scripts (see experiments below)
scripts/        Helper files to generate experiments scripts.
src/            The source code for the algorithm.
Project.toml    This file specifies required julia environment.
README.md       This is this file.

Installation

1. Julia version 1.7
2. The following command will download and install all required packages.

julia -e 'using Pkg; Pkg.activate("."); Pkg.instantiate(); Pkg.precompile();'

Experiments

Please navigate to bin/README.md for details.