Convolutional Sequence to Sequence Learning

666 indexed citations

Abstract

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About

This paper, published in 2017, received 666 indexed citations. Written by Jonas Gehring, Michael Auli, David Grangier, Denis Yarats and Yann Dauphin covering the research area of Artificial Intelligence. It is primarily cited by scholars working on Artificial Intelligence (545 citations), Computer Vision and Pattern Recognition (301 citations) and Signal Processing (70 citations). Published in International Conference on Machine Learning.

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Countries where authors are citing Convolutional Sequence to Sequence Learning

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This map shows the geographic impact of Convolutional Sequence to Sequence Learning. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Convolutional Sequence to Sequence Learning with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Convolutional Sequence to Sequence Learning more than expected).

Fields of papers citing Convolutional Sequence to Sequence Learning

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Convolutional Sequence to Sequence Learning. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Convolutional Sequence to Sequence Learning.

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This paper is also available at doi.org/w4473277.

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