arXiv stat.ML
· Papers
Integrating Background Knowledge for Scalable Causal Discovery
arXiv:2607.10456v1 Announce Type: new Abstract: Expert background knowledge is often available in practical applications of causal discovery. Such constraints on the true causal graph can help causal discovery in terms of identifiability of causal effects and accuracy of the learned structure, but also in reducing the