Search Packages

bnlearn

Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inferences, Sampling methods.

bamt

Repository of a data modeling and analysis tool based on Bayesian networks

thegolem

Graph Optimiser for Learning and Evolution of Models

dagma

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"

avici

Amortized Inference for Causal Structure Learning, NeurIPS 2022

bamt-light

data modeling and analysis tool based on Bayesian networks

dibs-lib

DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021

qdscreen

Quasi-determinism screening for fast Bayesian Network Structure Learning (from T.Rahier's PhD thesis, 2018)

bnclassify

bnlearn

iscm

A data generating package implemented as part of 'Standardizing Structural Causal Models'