Ghost Attractor Networks are theoretically derived dynamical decoders that impose basin-attractor geometry on latent space via potential-drift dynamics, enabling efficient multi-modal sequential generation and closed-loop control.
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Ghost Attractor Networks: Basin-Structured Dynamical Decoders for Closed-Loop Sequential Generation
Ghost Attractor Networks are theoretically derived dynamical decoders that impose basin-attractor geometry on latent space via potential-drift dynamics, enabling efficient multi-modal sequential generation and closed-loop control.