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Explicit Interaction Architectures for Dynamical Learning: A Controlled Study of Structural Inductive Bias
We investigate a structure-first approach to dynamical learning in which the organization of stateful interactions is prescribed explicitly rather than left entirely to a generic recurrent parameterization. We introduce causal recurrent units built from an ordered sequence of local, state-modulated
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