Federico Errica

About

Federico Errica is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Federico Errica has authored 17 papers receiving a total of 260 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 4 papers in Molecular Biology. Recurrent topics in Federico Errica’s work include Advanced Graph Neural Networks (10 papers), Graph Theory and Algorithms (4 papers) and Complex Network Analysis Techniques (3 papers). Federico Errica is often cited by papers focused on Advanced Graph Neural Networks (10 papers), Graph Theory and Algorithms (4 papers) and Complex Network Analysis Techniques (3 papers). Federico Errica collaborates with scholars based in Italy, Germany and Japan. Federico Errica's co-authors include Alessio Micheli, Davide Bacciu, Marco Podda, Raffaello Potestio, Marco Giulini, Roberto Menichetti, Makoto Takamoto, Nicolò Navarin, Mathias Niepert and Johannes Kästner and has published in prestigious journals such as The Journal of Chemical Physics, Neurocomputing and Neural Networks.

In The Last Decade

Co-authorship network of co-authors of Federico Errica i

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Fields of papers citing papers by Federico Errica

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Federico Errica. 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 Federico Errica. The network helps show where Federico Errica may publish in the future.

Countries citing papers authored by Federico Errica

Since Specialization

Citations

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