52 citations · 255 across the 21 of their papers we have counts for
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cs.LG2019★ 44 cited
Are Transformers universal approximators of sequence-to-sequence functions?
Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat +2
Despite the widespread adoption of Transformer models for NLP tasks, the expressive power of these models is not well-understood. In this paper, we establish that Transformer model…
cs.LG2019★ 5 cited
Are deep ResNets provably better than linear predictors?
Chulhee Yun, Suvrit Sra, Ali Jadbabaie
Recent results in the literature indicate that a residual network (ResNet) composed of a single residual block outperforms linear predictors, in the sense that all local minima in…