R Package for Simultaneous Multi-Bias Analysis
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Updated
May 25, 2024 - R
R Package for Simultaneous Multi-Bias Analysis
Desktop visual editor of causal models written in JavaScript using Electron and D3
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
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.
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
Causality reading group
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.
Time-concordant event cascades in the pathogenesis of adverse hepatic effects derived using transcriptomics and histopathology data from longitudinal studies in rats.
Work done for University of Pittsburgh course "Principles of Data Science" (STAT 1261) with Dr. Junshu Bao in Fall semester of 2018.
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