Language modeling with gated convolutional networks
- Journal
- International Conference on Machine Learning
In The Last Decade
doi.org/w7437141 →Countries where authors are citing Language modeling with gated convolutional networks
This map shows the geographic impact of Language modeling with gated convolutional networks. 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 Language modeling with gated convolutional networks with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Language modeling with gated convolutional networks more than expected).
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This network shows the impact of Language modeling with gated convolutional networks. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Language modeling with gated convolutional networks.
About Language modeling with gated convolutional networks
This paper, published in 2017, received 454 indexed citations . Written by Yann Dauphin, Angela Fan, Michael Auli and David Grangier covering the research area of Artificial Intelligence and Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Artificial Intelligence (313 citations), Computer Vision and Pattern Recognition (161 citations) and Signal Processing (139 citations). Published in International Conference on Machine Learning.
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This paper is also available at doi.org/w7437141.