Differentiable Structure Learning for Cyclic Linear Gaussian Models with Latent Confounders.

arXiv:2609.38618v1 Announce Type: cross Abstract: We study causal structure learning from observational data in linear Gaussian structural causal models in the presence of directed cycles and an unknown number of exogenous latent confounders, bounded by a give