Juan L. Gamella

Active Invariant Causal Prediction: Experiment Selection through\n Stability

2020 · arXiv (Cornell University)

A fundamental difficulty of causal learning is that causal models can\ngenerally not be fully identified based on observational data only.\nInterventional data, that is, data originating from different experimental\nenvironments, improves identifiability. However, the improvement depends\ncritically on …