CausalGPSLC.jl

Causal Inference using Gaussian Processes with Structured Latent Confounders. Estimate treatment effects with Gaussian processes.
Author KDL-umass
Popularity
6 Stars
Updated Last
4 Months Ago
Started In
January 2022

CausalGPSLC: Gaussian Processes with Structured Latent Confounders

Stable Dev CI codecov

Description

This project provides a software interface in Julia for performing causal inference using Gaussian processes with structured latent confounders, as defined in the ICML 2020 paper.

Contributing

Please review the contribution instructions in the contributing page.

Acknowledgements

The original paper was published by Sam Witty, Kenta Takatsu, David Jensen, and Vikash Mansinghka in 2020. As the git history indicates, Sam Witty (switty) and Kenta Takatsu (Kenta426) made the original contributions to the code during their research process.

This package was compiled by Jack Kenney in 2022 under the guidance of Sam Witty and David Jensen.