Welcome to the Join Bayes Net (JBN) system!
Methods for discovering causal dependencies from data have been the focus of decades of work in AI, statistics, philosophy, and social science. However, the vast majority of this work has focused on propositional data and do not address casual dependencies between entities and relationships in relational data.
Join Bayes Nets is a software package providing a series of learning algorithms for statistical relational learning and probabilistic inference. The Bayes Net code basis was the open-source The TETRAD Project. TETRAD permits users to generate directed graphical statistical/causal models for non relational data. We extend their work to allow learning in the relational setting where it is possible to capture causal dependencies on relational data.