A bit-by-bit Guide to the Equations Governing Differentiable Neural Computers

jaspock.github.io

The concept of a differentiable neural computer was first introduced back in 2016 in the DeepMind paper "Hybrid computing using a neural network with dynamic external memory", it holds the potential to apply neural networks to a number of algorithmic task that have hitherto been inaccessible. This great post delves into the nitty gritty mathematical foundations of DNC and explains the architecture of the memory augmented model in detail. Highly recommended.

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