RSL

Paper: Learning Bayesian Networks in the Presence of Structural Side Information

"On data" folder:
RSL_D.m : RSL-diamond-free function
RSL_W.m : RSL-bounded-clique-number function
Demo_RealWorld_Graph.m: This file generates a dataset on a real-world structure and call the RSL functions
Demo_ Random_Graph.m: This file generates a dataset on Erdos-Renyi random graph and call the RSL functions
ComputeMb_TC: Compute the Markov boundaries using TC algorithm
CI_tests: Checks the conditional independencies (CI) tests for linear-Gaussian models.

"Oracle CI tests" folder:
RSL_D_oracle.m : RSL-diamond-free function in oracle setting
RSL_W_oracle.m : RSL-bounded-clique-number function in oracle setting
Demo_RealWorld_Graph.m: This file loads a real-world structure and call the RSL functions in oracle setting
Demo_ Random_Graph.m: This file generates a Erdos-Renyi random graph and call the RSL functions
ComputeMb_oracle: Compute the true Markov boundaries using G
dsep: Checks a d-separation in the graph