Discovery

Causal discovery: LiNGAM identifiability, linear disentanglement, and invariant prediction tools for recovering structure from distributional and environment-shift information.

Invariant­Prediction 46 core · 27 supporting · 6 submodules Entry point for the formalization of Peters, Bühlmann & Meinshausen, *Causal inference using invariant prediction: identification and confidence intervals* (JRSS-B 2016, arXiv:1501.01332). Linear­Disentanglement 30 core · 56 supporting · 7 submodules Entry point for the formalization of Squires, Seigal, Bhate & Uhler, *Linear Causal Disentanglement via Interventions* (ICML 2023, arXiv:2211.16467). Li­NGAM 6 core · 0 supporting · 3 submodules Linear non-Gaussian acyclic model identification: permutation uniqueness, generalized-permutation algebra, kurtosis-based column support, and the LiNGAM identifiability theorem.