Search Packages

pgmpy

Python Toolkit for Causal and Probabilistic Reasoning

causal-learn

Causal Discovery in Python. Learning causality from data.

lingam

Python package for causal discovery based on LiNGAM.

cdt

Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.

gcastle

Trustworthy AI related projects

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"

ylearn

YLearn, a pun of "learn why", is a python package for causal inference

esa-2scm

ESA-2SCM Python Package for Causal Discovery

copent

Estimating Copula Entropy (Mutual Information), Transfer Entropy (Conditional Mutual Information), and the statistics for multivariate normality test and two-sample test, and change point detection in Python

scmopy

scmopy: Distribution-Agnostic Structural Causal Models Optimization in Python

avici

Amortized Inference for Causal Structure Learning, NeurIPS 2022

pytrad

Causal Discovery in Python. Learning causality from data.

jax-pcmci

High-performance causal discovery using PCMCI algorithms with JAX acceleration

dagsampler

Configurable causal DAG simulator for synthetic mixed-type data and CI test benchmarks

pypcalg

A Python implementation of the original PC algorithm.

seq2cause

Sample- And Population-Level Causal Discovery from Event Sequences using Autoregressive Models

cits

Python package for CITS algorithm: Causal inference from time series data

pyparcs

A simulation package for causal methods

pgmpy-rcr

Python Toolkit for Causal and Probabilistic Reasoning

fpcmci

A causal discovery Python package

culingam

CULiNGAM accelerates LiNGAM analysis on GPUs.

causationentropy

Implementation of Causation Entropy from Clarkson Center for Complex Systems Science (C3S2)

py-causalflow

CausalFlow: a Unified Framework for Causality in Time-Series

iscm

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