Intervene, Calibrate, Discover: Learning Causal Structure from Pixels.

arXiv:2610.34711v1 Announce Type: new Abstract: Learning high-level causal variables from low-level observations is a central problem for artificial intelligence. With known node semantics but an unknown graph, visual readout errors can misalign model settings