Marc’Aurelio Ranzato

46 papers and 9.8k indexed citations i.

About

Marc’Aurelio Ranzato is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Marc’Aurelio Ranzato has authored 46 papers receiving a total of 9.8k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Artificial Intelligence, 26 papers in Computer Vision and Pattern Recognition and 5 papers in Signal Processing. Recurrent topics in Marc’Aurelio Ranzato’s work include Topic Modeling (17 papers), Natural Language Processing Techniques (14 papers) and Domain Adaptation and Few-Shot Learning (9 papers). Marc’Aurelio Ranzato is often cited by papers focused on Topic Modeling (17 papers), Natural Language Processing Techniques (14 papers) and Domain Adaptation and Few-Shot Learning (9 papers). Marc’Aurelio Ranzato collaborates with scholars based in United States, Israel and Canada. Marc’Aurelio Ranzato's co-authors include Lior Wolf, Yaniv Taigman, Ming Yang, Greg S. Corrado, Y-Lan Boureau, Jeff Dean, Yann LeCun, Tomáš Mikolov, Ludovic Denoyer and Guillaume Lample and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Trends in Cognitive Sciences and Applied and Computational Harmonic Analysis.

In The Last Decade

Co-authorship network of co-authors of Marc’Aurelio Ranzato i

Fields of papers citing papers by Marc’Aurelio Ranzato

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marc’Aurelio Ranzato. 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 Marc’Aurelio Ranzato. The network helps show where Marc’Aurelio Ranzato may publish in the future.

Countries citing papers authored by Marc’Aurelio Ranzato

Since Specialization
Citations

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