activity
20162026
most citedOne Model To Learn Them All

258 citations · 1.1k across the 13 of their papers we have counts for

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Showing 2018Show all

8 papers · 1 filter

cs.LG2018★ 51 cited

Mesh-TensorFlow: Deep Learning for Supercomputers

Noam Shazeer, Youlong Cheng, Niki Parmar +9

Batch-splitting (data-parallelism) is the dominant distributed Deep Neural Network (DNN) training strategy, due to its universal applicability and its amenability to Single-Program…

cs.LG2018★ 73 cited

Music Transformer

Cheng-Zhi Anna Huang, Ashish Vaswani, Jakob Uszkoreit +7

Music relies heavily on repetition to build structure and meaning. Self-reference occurs on multiple timescales, from motifs to phrases to reusing of entire sections of music, such…

cs.LG2018

Relational inductive biases, deep learning, and graph networks

Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst +24

Artificial intelligence (AI) has undergone a renaissance recently, making major progress in key domains such as vision, language, control, and decision-making. This has been due, i…

cs.LG2018★ 54 cited

Theory and Experiments on Vector Quantized Autoencoders

Aurko Roy, Ashish Vaswani, Arvind Neelakantan +1

Deep neural networks with discrete latent variables offer the promise of better symbolic reasoning, and learning abstractions that are more useful to new tasks. There has been a su…

cs.CL2018

Self-Attention with Relative Position Representations

Peter Shaw, Jakob Uszkoreit, Ashish Vaswani

Relying entirely on an attention mechanism, the Transformer introduced by Vaswani et al. (2017) achieves state-of-the-art results for machine translation. In contrast to recurrent…

cs.LG2018★ 14 cited

Tensor2Tensor for Neural Machine Translation

Ashish Vaswani, Samy Bengio, Eugene Brevdo +10

Tensor2Tensor is a library for deep learning models that is well-suited for neural machine translation and includes the reference implementation of the state-of-the-art Transformer…

cs.LG2018★ 169 cited

Fast Decoding in Sequence Models using Discrete Latent Variables

Łukasz Kaiser, Aurko Roy, Ashish Vaswani +4

Autoregressive sequence models based on deep neural networks, such as RNNs, Wavenet and the Transformer attain state-of-the-art results on many tasks. However, they are difficult t…

cs.CV2018★ 227 cited

Image Transformer

Niki Parmar, Ashish Vaswani, Jakob Uszkoreit +4

Image generation has been successfully cast as an autoregressive sequence generation or transformation problem. Recent work has shown that self-attention is an effective way of mod…