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Role-Specific Predictive Geometries for Nonstationary Multivariate Graph-Signal Forecasting

arXiv · AI, language, vision and robotics · article · Sep 6, 2026 · UTC

Forecasting multivariate graph signals is challenging when node-level trajectories are nonstationary but stable relations persist across nodes and features. In an error-correction representation, long-run equilibrium restoration and short-run transient propagation represent different predictive roles and need not share a common cross-feature geometry. We introduce role-specific predictive geometries in which directed Long relations act on estimated equilibrium coordinates, whereas directed Short relations act on lagged differences. Matrix-valued Long responses mix equilibrium coordinates befor

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