David Alvarez-Melis

About

David Alvarez-Melis is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Materials Chemistry. According to data from OpenAlex, David Alvarez-Melis has authored 12 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 1 paper in Materials Chemistry. Recurrent topics in David Alvarez-Melis’s work include Topic Modeling (7 papers), Natural Language Processing Techniques (5 papers) and Machine Learning and Data Classification (4 papers). David Alvarez-Melis is often cited by papers focused on Topic Modeling (7 papers), Natural Language Processing Techniques (5 papers) and Machine Learning and Data Classification (4 papers). David Alvarez-Melis collaborates with scholars based in United States and Switzerland. David Alvarez-Melis's co-authors include Tommi Jaakkola, Martin Saveski, Tatsunori Hashimoto, Stefanie Jegelka, Nicolò Fusi, Guang-He Lee, Charlotte Bunne, Andreas Krause, Youssef Mroueh and Wengong Jin and has published in prestigious journals such as Transactions of the Association for Computational Linguistics, arXiv (Cornell University) and neural information processing systems.

In The Last Decade

Co-authorship network of co-authors of David Alvarez-Melis i

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Fields of papers citing papers by David Alvarez-Melis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Alvarez-Melis. 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 David Alvarez-Melis. The network helps show where David Alvarez-Melis may publish in the future.

Countries citing papers authored by David Alvarez-Melis

Since Specialization

Citations

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