Physical Simulators as Do-Operators: Causal Discovery under Latent Confounders for AI-for-Science

ArXi:2605.07467v1 Announce Type: cross Existing interventional causal discovery methods -- IGSP, DCDI, ENCO -- assume causal sufficiency (no latent confounders) and rely on virtual interventions in synthetic simulators. In AI-for-Science settings such as molecular design and materials science, latent confounders are ubiquitous and real interventions (e.g., physics-based simulations) require hours to days per data point.