Diana Borsa

About

Diana Borsa is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Networks and Communications. According to data from OpenAlex, Diana Borsa has authored 8 papers receiving a total of 80 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 2 papers in Computational Theory and Mathematics and 1 paper in Computer Networks and Communications. Recurrent topics in Diana Borsa’s work include Reinforcement Learning in Robotics (7 papers), Evolutionary Algorithms and Applications (1 paper) and Adaptive Dynamic Programming Control (1 paper). Diana Borsa is often cited by papers focused on Reinforcement Learning in Robotics (7 papers), Evolutionary Algorithms and Applications (1 paper) and Adaptive Dynamic Programming Control (1 paper). Diana Borsa collaborates with scholars based in United Kingdom, United States and Canada. Diana Borsa's co-authors include André Barreto, David Silver, Shaobo Hou, Doina Precup, Matteo Hessel, Tom Schaul, Yoram Bachrach, Daniel J. Mankowitz, Hado van Hasselt and Rémi Munos and has published in prestigious journals such as Proceedings of the National Academy of Sciences, arXiv (Cornell University) and International Conference on Machine Learning.

In The Last Decade

Co-authorship network of co-authors of Diana Borsa i

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Fields of papers citing papers by Diana Borsa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Diana Borsa. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Diana Borsa. The network helps show where Diana Borsa may publish in the future.

Countries citing papers authored by Diana Borsa

Since Specialization

Citations

This map shows the geographic impact of Diana Borsa's research. 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 Diana Borsa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Diana Borsa more than expected).

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.

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