scm

Beagle is a git-compatible source control management system that leverages HTTP URIs and verbs to provide a simpler, more orthogonal set of operations for complex git workflows like merging and rebasing.

This paper evaluates the practical effectiveness of Markov boundaries for tabular prediction, finding that while theoretically optimal, current causal discovery methods fail to consistently improve predictive performance due to computational limitations and mismatched optimization goals.