Liva Ralaivola

About

Liva Ralaivola is a scholar working on Artificial Intelligence, Computational Mechanics and Computational Theory and Mathematics. According to data from OpenAlex, Liva Ralaivola has authored 22 papers receiving a total of 859 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 5 papers in Computational Mechanics and 5 papers in Computational Theory and Mathematics. Recurrent topics in Liva Ralaivola’s work include Sparse and Compressive Sensing Techniques (5 papers), Machine Learning and Algorithms (4 papers) and Computational Drug Discovery Methods (4 papers). Liva Ralaivola is often cited by papers focused on Sparse and Compressive Sensing Techniques (5 papers), Machine Learning and Algorithms (4 papers) and Computational Drug Discovery Methods (4 papers). Liva Ralaivola collaborates with scholars based in France, United States and Canada. Liva Ralaivola's co-authors include Pierre Baldi, S. Joshua Swamidass, Florence d’Alché–Buc, Hiroto Saigo, Samuele Bottani, Jacques Mallet, Aurélien Mazurie, Jonathan H. Chen, Jocelyne Bruand and Pierre Mahé and has published in prestigious journals such as Bioinformatics, PLoS ONE and IEEE Transactions on Information Theory.

In The Last Decade

Co-authorship network of co-authors of Liva Ralaivola i

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Fields of papers citing papers by Liva Ralaivola

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Liva Ralaivola

Since Specialization

Citations

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