Optimization-Free Topological Sort for Causal Discovery via the Schur Complement of Score Jacobians

ArXi:2604.25295v1 Announce Type: new Continuous causal discovery typically couples representation learning with structural optimization via non-convex acyclicity penalties, which subjects solvers to local optima and restricts scalability in high-dimensional regimes. We propose a decoupled paradigm that shifts the causal discovery bottleneck from non-convex optimization to statistical score estimation. We