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Let me make sure I understand: rather than using gates, each step explicitly takes a weight average of all past steps using attention.

What is the training speed of this network? Computation seems to scale at N^2 rather than N.

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EDIT: The attention mechanism is nothing more than a weighted average. The weighted average is computed as a running average by saving the numerator and denominator terms at each step.

I hope the description in the paper is clear. You can follow the ARXIV link in the README. Skip straight to section 2 for the details of the model

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