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Differentiable neural computer
Artificial neural network architecture / From Wikipedia, the free encyclopedia
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In artificial intelligence, a differentiable neural computer (DNC) is a memory augmented neural network architecture (MANN), which is typically (but not by definition) recurrent in its implementation. The model was published in 2016 by Alex Graves et al. of DeepMind.[1]
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