Improving the speed of neural networks on CPUs
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doi.org/w45793900 →Countries where authors are citing Improving the speed of neural networks on CPUs
This map shows the geographic impact of Improving the speed of neural networks on CPUs. 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 Improving the speed of neural networks on CPUs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Improving the speed of neural networks on CPUs more than expected).
Fields of papers citing Improving the speed of neural networks on CPUs
This network shows the impact of Improving the speed of neural networks on CPUs. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Improving the speed of neural networks on CPUs.
About Improving the speed of neural networks on CPUs
This paper, published in 2011, received 384 indexed citations . Written by Vincent Vanhoucke, Andrew Senior and M. Mao covering the research area of Hardware and Architecture and Artificial Intelligence. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (240 citations), Artificial Intelligence (204 citations), Electrical and Electronic Engineering (98 citations), Signal Processing (63 citations) and Hardware and Architecture (37 citations).
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/w45793900.