Proceedings of the 19th International Conference on Artificial Intelligence and Statistics 2016
- Authors
- Iain MurrayMatthew Graham
In The Last Decade
doi.org/w75826180 →Countries where authors are citing Proceedings of the 19th International Conference on Artificial Intelligence and Statistics 2016
This map shows the geographic impact of Proceedings of the 19th International Conference on Artificial Intelligence and Statistics 2016. 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 Proceedings of the 19th International Conference on Artificial Intelligence and Statistics 2016 with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Proceedings of the 19th International Conference on Artificial Intelligence and Statistics 2016 more than expected).
Fields of papers citing Proceedings of the 19th International Conference on Artificial Intelligence and Statistics 2016
This network shows the impact of Proceedings of the 19th International Conference on Artificial Intelligence and Statistics 2016. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Proceedings of the 19th International Conference on Artificial Intelligence and Statistics 2016.
About Proceedings of the 19th International Conference on Artificial Intelligence and Statistics 2016
This paper, published in 2016, received 1.5k indexed citations . Written by Iain Murray and Matthew Graham. It is primarily cited by scholars working on Artificial Intelligence (930 citations), Computer Vision and Pattern Recognition (254 citations) and Information Systems (151 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/w75826180.