Jakob Uszkoreit
One of the eight authors of the 2017 transformer paper "Attention Is All You Need", then at Google Research; per the paper's own contribution note, proposed replacing recurrent networks with self-attention and started the effort to evaluate the idea.
Jakob Uszkoreit did not write this page. What is this?
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Where they publish
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Beliefs
Korrents What they believe 3 beliefs — each backed by an exact quote.
Each is a — compiled by korrents.com, not by them: the one-line wordings are korrents', the quotes are theirs.
Recent
Sequence transduction can use a simple architecture based solely on attention, without recurrence or convolutions.
We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely.
Attention is all you need Said 12 Jun 2017
A transduction model can rely entirely on self-attention for input and output representations without sequence-aligned RNNs or convolution.
To the best of our knowledge, however, the Transformer is the first transduction model relying entirely on self-attention to compute representations of its input and output without using sequence-aligned RNNs or convolution.
Attention is all you need Said 12 Jun 2017
Self-attention can yield more interpretable models.
As side benefit, self-attention could yield more interpretable models.
Attention is all you need Said 12 Jun 2017
Beliefs others hold too
Sequence transduction can use a simple architecture based solely on attention, without recurrence or convolutions. 8 hold this
We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely.
Attention is all you need Said 12 Jun 2017
A transduction model can rely entirely on self-attention for input and output representations without sequence-aligned RNNs or convolution. 8 hold this
To the best of our knowledge, however, the Transformer is the first transduction model relying entirely on self-attention to compute representations of its input and output without using sequence-aligned RNNs or convolution.
Attention is all you need Said 12 Jun 2017
Self-attention can yield more interpretable models. 8 hold this
As side benefit, self-attention could yield more interpretable models.
Attention is all you need Said 12 Jun 2017
What is a korrent?
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About the English under a post
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