Causal inference, graphical models and structure learning in Julia
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Updated
Mar 25, 2025 - Julia
Causal inference, graphical models and structure learning in Julia
Algorithms for quantifying associations, independence testing and causal inference from data.
A suite of Julia packages for difference-in-differences
Taking causal inference to the extreme!
Causal Inference with Invariant Prediction
A Julia implementation of the Targeted Minimum Loss-based Estimation
Regression-based multi-period difference-in-differences with heterogenous treatment effects
Base package for DiffinDiffs.jl
Causal Inference using Gaussian Processes with Structured Latent Confounders. Estimate treatment effects with Gaussian processes.
Synthetic difference in differences - Julia implementation of https://synth-inference.github.io/synthdid/
Fast Inference of Biological Networks from Directed Regulations (Findr) in Julia
Source code for the paper "Lifted Causal Inference in Relational Domains" (CLeaR 2024)
A molecular Mendelian Randomization tool
Contains the LLCB method from Weinstock* and Arce* et al., 2023
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