36 citations · 85 across the 3 of their papers we have counts for
3 papers
Causal Discovery Toolbox: Uncover causal relationships in Python
Diviyan Kalainathan, Olivier Goudet
This paper presents a new open source Python framework for causal discovery from observational data and domain background knowledge, aimed at causal graph and causal mechanism mode…
Structural Agnostic Modeling: Adversarial Learning of Causal Graphs
Diviyan Kalainathan, Olivier Goudet, Isabelle Guyon +2
A new causal discovery method, Structural Agnostic Modeling (SAM), is presented in this paper. Leveraging both conditional independencies and distributional asymmetries, SAM aims t…
Causal Generative Neural Networks
Olivier Goudet, Diviyan Kalainathan, Philippe Caillou +3
We present Causal Generative Neural Networks (CGNNs) to learn functional causal models from observational data. CGNNs leverage conditional independencies and distributional asymmet…