58 citations · 255 across the 13 of their papers we have counts for
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cs.LG2021★ 6 cited
Understanding How Encoder-Decoder Architectures Attend
Kyle Aitken, Vinay V Ramasesh, Yuan Cao +1
Encoder-decoder networks with attention have proven to be a powerful way to solve many sequence-to-sequence tasks. In these networks, attention aligns encoder and decoder states an…
cs.LG2020★ 4 cited
The geometry of integration in text classification RNNs
Kyle Aitken, Vinay V. Ramasesh, Ankush Garg +3
Despite the widespread application of recurrent neural networks (RNNs) across a variety of tasks, a unified understanding of how RNNs solve these tasks remains elusive. In particul…
cs.LG2020★ 8 cited
On the asymptotics of wide networks with polynomial activations
Kyle Aitken, Guy Gur-Ari
We consider an existing conjecture addressing the asymptotic behavior of neural networks in the large width limit. The results that follow from this conjecture include tight bounds…