Large Scale Distributed Deep Networks
Impact in
Classified as
- Journal
- Neural Information Processing Systems
In The Last Decade
doi.org/w10039850 →Countries where authors are citing Large Scale Distributed Deep Networks
This map shows the geographic impact of Large Scale Distributed Deep 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 Large Scale Distributed Deep Networks with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Large Scale Distributed Deep Networks more than expected).
Fields of papers citing Large Scale Distributed Deep Networks
This network shows the impact of Large Scale Distributed Deep Networks. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Large Scale Distributed Deep Networks.
About Large Scale Distributed Deep Networks
This paper, published in 2012, received 1.7k indexed citations . Written by Jay B. Dean, Greg S. Corrado, Rajat Monga, Kai Chen, Matthieu Devin, M. Mao, Marc’Aurelio Ranzato, Andrew Senior, Paul A. Tucker and Ke Yang covering the research area of Artificial Intelligence and Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Artificial Intelligence (1.2k citations), Computer Vision and Pattern Recognition (717 citations), Computer Networks and Communications (356 citations), Electrical and Electronic Engineering (194 citations) and Signal Processing (180 citations). Published in Neural Information Processing Systems.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
This paper is also available at doi.org/w10039850.