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
rath
Next generation of automated data exploratory analysis and visualization platform.
DPI
🛸 The Directed Prediction Index (DPI): Quantifying Relative Endogeneity of Outcome Versus Predictor Variables.
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.
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).