Discover juangamella/aicp Open Source project

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Python
Created over 4 years ago
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Code to reproduce the experimental results from the paper "Active Invariant Causal Prediction: Experiment Selection Through Stability", by Juan L Gamella and Christina Heinze-Deml.

icp

Python implementation of the Invariant Causal Prediction (ICP) algorithm, from the 2015 paper "Causal inference using invariant prediction: identification and confidence intervals" by Jonas Peters, Peter Bühlmann and Nicolai Meinshausen.

Python

ges

Python implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Search" by David Maxwell Chickering.

Python

sempler

Framework to generate observational and interventional samples from structural equation models (SEMs)

Python

gies

Python implementation of the GIES algorithm for causal discovery, from the 2012 paper "Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs" by Alain Hauser and Peter Bühlmann.

Python

ut-lvce

Python implementation of the UT-LVCE algorithms from the 2022 paper "Perturbations and Causality in Gaussian Latent Variable Models", by A. Taeb, JL. Gamella, C. Heinze-Deml and P. Bühlmann.

Python

gnies

Python implementation of the GnIES algorithm from the 2022 paper "Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions" by Gamella et al.

Python

stars

Python implementation of the StARS algorithm: "Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models" by Han Liu, Kathryn Roeder, Larry Wasserman, 2010

Python

vistools

A signal-processing and visualization suite written in C and OpenGL

juangamella/aicp

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