Causal Process Models: Reframing Dynamic Causal Graph Discovery as a Reinforcement Learning Problem

ArXi:2507.13920v2 Announce Type: replace Most neural models of causality assume static causal graphs, failing to capture the dynamic and sparse nature of physical interactions where causal relationships emerge and dissolve over time. We