Near-Optimal Experiment Design in Linear non-Gaussian Cyclic Models
NeurIPSSpotlight2025
TL;DR
We study the problem of causal structure learning from a combination of observational and interventional data generated by a linear non-Gaussian structural equation model that might contain cycles…
Opening excerpt from the authors’ abstract. source
Read the paper
Topics
causal
← All NeurIPS 2025 Spotlight papers · Browse the whole archive