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5 search results found

Dowhy ⭐ 6,730

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

Toolbox ⭐ 104

A Java Toolbox for Scalable Probabilistic Machine Learning

A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization"

Benchpress ⭐ 52

A Snakemake workflow to run and benchmark structure learning (a.k.a. causal discovery) algorithms for probabilistic graphical models.

Sparsebn ⭐ 37

Software for learning sparse Bayesian networks

Easy Factor Graph ⭐ 24

General purpose C++ library for managing discrete factor graphs

Linear Gaussian Bayesian Networks - Inference, Parameter Learning and Representation. 🖧

Pythonbrmltoolbox ⭐ 10

Python 3.7 version of David Barber's MATLAB BRMLtoolbox

Junction Tree ⭐ 10

The junction tree algorithm for (discrete) factor graphs

Inference in Bayesian Networks with R

Bayesian Bricks ⭐ 6

Basic building blocks in Bayesian statistics.

Ccdralgorithm ⭐ 5

Structure learning for Bayesian networks using the CCDr algorithm.

1-5 of 5 search results

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