juangamella

Juan L. Gamella's repositories

ges

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

Language:PythonBSD-3-Clause48 2 2

aicp

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.

Language:Python19 40

causal-chamber

Dataset repository for the 2024 paper "The Causal Chambers: Real Physical Systems as a Testbed for AI Methodology" by Juan L. Gamella, Jonas Peters and Peter Bühlmann.

Language:PythonMIT17 10

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.

Language:PythonBSD-3-Clause1700

sempler

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

Language:PythonBSD-3-Clause11 2 3

causal-chamber-paper

Code to reproduce the case studies of the 2024 paper "The Causal Chambers: Real Physical Systems as a Testbed for AI Methodology" by Juan L. Gamella, Jonas Peters and Peter Bühlmann.

Language:Jupyter NotebookMIT10 10

abcd

Code to reproduce the results comparing ABCD to A-ICP in the paper "Active Invariant Causal Prediction: Experiment Selection through Stability", by Juan L Gamella and Christina Heinze-Deml.

Language:Python6 10

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.

Language:PythonBSD-3-Clause4 10

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.

Language:PythonBSD-3-Clause3 10

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.

Language:PythonBSD-3-Clause2 10

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

Language:PythonBSD-3-Clause200

vistools

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

Language:CBSD-3-Clause1 1 3

gnies-paper

Experiments repository for the 2022 paper "Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions" by Juan L. Gamella, Armeen Taeb, Christina Heinze-Deml and Peter Bühlmann.

Language:Jupyter NotebookBSD-3-Clause010

slate

Beautiful static documentation for your API

Language:JavaScriptNOASSERTION010

ut-lvce-paper

Experiments repository for the paper "Perturbations and Causality in Gaussian Latent Variable Models", by A. Taeb, JL. Gamella, C. Heinze-Deml and P. Bühlmann.

Language:Jupyter NotebookBSD-3-Clause020