pycid
Library for graphical models of decision making, based on pgmpy and networkx
nl-causal-representations
This is the code for the paper Jacobian-based Causal Discovery with Nonlinear ICA, demonstrating how identifiable representations (particularly, with Nonlinear ICA) can be used to extract the causal graph from an underlying structural equation model (SEM).
https://github.com/py-why/dowhy
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.
https://github.com/biomedsciai/causallib
A Python package for modular causal inference analysis and model evaluations
msapy
Hopefully, a compact and general-purpose Python package for Multiperturbation Shapley value Analysis (MSA).
pywhy-graphs
[Experimental] Causal graphs that are networkx-compliant for the py-why ecosystem.
copent
R package for estimating copula entropy (mutual information), transfer entropy (conditional mutual information), and the statistic for multivariate normality test and two-sample test
https://github.com/andrewtavis/causeinfer
Machine learning based causal inference/uplift in Python
https://github.com/alan-turing-institute/causal-cyber-defence
This repository contains glue-code necessary to run dynamic Causal Bayesian optimisation within the Yawning Titan cyber-simulation environment.
https://github.com/asjadnaqvi/climate-econ
A repository for tracking developments in the climate/environmental/ecological economics literature
https://github.com/berenslab/disentangling-retinal-images
This repository contains the code for the paper "Disentangling representations of retinal images with generative models".
Causality-in-Trustworthy-Machine-Learning
The repository contains lists of papers on causality and how relevant techniques are being used to further enhance deep learning era computer vision solutions.
rath
Next generation of automated data exploratory analysis and visualization platform.
https://github.com/ai4healthuol/causalconceptts
Repository for the paper 'CausalConceptTS: Causal Attributions for Time Series Classification using High Fidelity Diffusion Models'.
agrum
This repository is a mirror. If you want to raise an issue or contact us, we encourage you to do it on Gitlab (https://gitlab.com/agrumery/aGrUM).
DPI
🛸 The Directed Prediction Index (DPI): Quantifying Relative Endogeneity of Outcome Versus Predictor Variables.