Automatic differentiation in machine learning: a survey
- Journal
- Maynooth University ePrints and eTheses Archive (Maynooth University)
In The Last Decade
doi.org/w1013420 →Countries where authors are citing Automatic differentiation in machine learning: a survey
This map shows the geographic impact of Automatic differentiation in machine learning: a survey. 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 Automatic differentiation in machine learning: a survey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Automatic differentiation in machine learning: a survey more than expected).
Fields of papers citing Automatic differentiation in machine learning: a survey
This network shows the impact of Automatic differentiation in machine learning: a survey. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Automatic differentiation in machine learning: a survey.
About Automatic differentiation in machine learning: a survey
This paper, published in 2015, received 1.3k indexed citations . Written by Atılım Güneş Baydin, Barak A. Pearlmutter, Alexey Radul and Jeffrey Mark Siskind covering the research area of Artificial Intelligence. It is primarily cited by scholars working on Statistical and Nonlinear Physics (656 citations), Artificial Intelligence (310 citations) and Computational Mechanics (285 citations). Published in Maynooth University ePrints and eTheses Archive (Maynooth University).
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This paper is also available at doi.org/w1013420.