7 citations · 7 across the 5 of their papers we have counts for
3 papers · 1 filter
Efficient Latent Variable Causal Discovery: Combining Score Search and Targeted Testing
Joseph Ramsey, Bryan Andrews, Peter Spirtes
Learning causal structure from observational data is especially challenging when latent variables or selection bias are present. The Fast Causal Inference (FCI) algorithm addresses…
Choosing DAG Models Using Markov and Minimal Edge Count in the Absence of Ground Truth
Joseph D. Ramsey, Bryan Andrews, Peter Spirtes
We give a novel nonparametric pointwise consistent statistical test (the Markov Checker) of the Markov condition for directed acyclic graph (DAG) or completed partially directed ac…
Fast Scalable and Accurate Discovery of DAGs Using the Best Order Score Search and Grow-Shrink Trees
Bryan Andrews, Joseph Ramsey, Ruben Sanchez-Romero +2
Learning graphical conditional independence structures is an important machine learning problem and a cornerstone of causal discovery. However, the accuracy and execution time of l…