An index of algorithms for learning causality with data

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

A resource list for causality in statistics, data science and physics

Causal discovery algorithms and tools for implementing new ones

Hyper-geometric computational causality for Rust

💊 Comparing causality methods in a fair and just way.

Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.

causaleffect: R package for identifying causal effects.

Official PyTorch Implementation for "Causal Mode Multiplexer: A Novel Framework for Unbiased Multispectral Pedestrian Detection" in CVPR 2024

Predictive State Propensity Subclassification (PSPS): A causal deep learning algoritm in TensorFlow keras

Code for paper "A method for detecting causal relationships between industrial alarm variables using Transfer entropy and K2-Algorithm"

Implementations of var-sortability, sortnregress, and chain-orientation as presented in the article "Beware of the Simulated DAG": https://arxiv.org/abs/2102.13647.

[SDM'23] ML4C: Seeing Causality Through Latent Vicinity

MR-link and genome integration. genome_integration is a repository for the analysis of genomic data. Specifically, the repository implements the causal inference method MR-link, as well as other Mendelian randomization methods.

cfid: R package for identifying counterfactuals.

dosearch: R Package for Identifying General Causal Queries

This R package is based on the work presented in A. Jérolon et al., "Causal mediation analysis in presence of multiple mediators uncausally related".The work allowing multiple mediation analyzes with a survival outcome was largely developed with Arce Domingo. This work is presented in Domingo-Relloso et al., "Causal mediation for uncausally relate

A broadcast middleware service delivering messages in a causal order

Code library for training causal inference deep learning models with automatic hyperparameter optimization written in Tensorflow 2.

Hume's Guillotine: Beheading the social pseudo-sciences with the Algorithmic Information Criterion for CAUSAL model selection.

A Powerful Python Library for Causal Inference

Tutorials for the synthetic control method for causal inference using PyMC

Análise de Intervenção de Ansiedade com Descoberta Causal

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

Basic experimental set-up for the comparison of causal structure learning algorithms as shown in "Beware of the Simulated DAG".

Identifiability of AMP chain graph

Learning causal inference models, frameworks, IPTW and causal ML approaches

Accompanying repository for the paper “When to Trust: Causality-Aware Calibration for Accurate KG-RAG” by Jing Ren, Bowen Li, Ziqi Xu, Xikun Zhang, Haytham Fayek, and Xiaodong Li, published in The Web Conference 2026.

Incentivizing the production of the Universal Distribution from turing tape output using a mutual credit system

Your AI answers before it understands. Fathom Mode fixes that.