R Package for Simultaneous Multi-Bias Analysis
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Updated
Jul 14, 2024 - R
R Package for Simultaneous Multi-Bias Analysis
Desktop visual editor of causal models written in JavaScript using Electron and D3
Causal analysis and inference using observational and interventional dataset. It contains tools for graph structure recovery.
Awesome papers on Causal Inference
Used a data set of graduate school admission decisions to construct a Bayesian network, then explored causal relationships between different variables.
This repository serves as a research archive for the mini-project "Comparison of Gaussian graphical models (GGM) and Directed Cyclic Graph (DCG) Models as Causal Discovery Tools"
A dataset of news headlines for detecting causalities
R Code for graphical causal models including some undirected one. Models include LiNGAM, LOFS, Patel's tau, graphical lasso, and PC algorithm.
Code and figures for Sizes of Interventional Markov Equivalence Classes
JupyterLab renderer of dagitty causal diagrams
A high-performance implementation of Shpitser's ID algorithm for causal identification in Rust
Causal Abstraction of Neural Models Trained to Solve ReaSCAN
A PyTorch implementation of the "robust" synthetic control model
ImpactFlow is a Python Library for decision modeling based on causal decision models - in which levers and external factors of decisions feed into outcomes.
Simplifying audio and deep learning with PyTorch.
Causality reading group
Generating images of minority groups using latent SCM model in the Bidirectional Generative Model.
CausalVerse: An R toolkit expediting causal research & analysis. Streamlines complex methodologies, empowering users to unveil causal relationships with precision. Your go-to for insightful causality exploration.
A structure for representing possible states of a causal entity (such as plot, generalized character personality, aspects of natural language typological structure, etc.) taking into account the probabilities of facts
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