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CTNet introduces a novel neural architecture where computation is framed as the evolution of a persistent state rather than successive rewrites, incorporating re-entrant memory, multi-scale coherence, and projective output.
OpenAI research explores how nonlinear computation can emerge in deep linear networks, presenting theoretical and empirical analysis with code examples using TensorFlow.