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AugRelNet: Relation-Augmented Dynamics for Structure Discovery and Forecasting from Limited Data
Complex dynamics often arise from persistent interactions whose effects vary with the system state. We introduce AugRelNet for short- and medium-horizon trajectory forecasting from limited data. A shared learnable relation matrix explicitly routes source signals to targets, while evolving local feat
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