Marylou Gabrié

13 papers and 214 indexed citations i.

About

Marylou Gabrié is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Marylou Gabrié has authored 13 papers receiving a total of 214 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 5 papers in Statistical and Nonlinear Physics and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Marylou Gabrié’s work include Neural Networks and Applications (4 papers), Markov Chains and Monte Carlo Methods (3 papers) and Generative Adversarial Networks and Image Synthesis (3 papers). Marylou Gabrié is often cited by papers focused on Neural Networks and Applications (4 papers), Markov Chains and Monte Carlo Methods (3 papers) and Generative Adversarial Networks and Image Synthesis (3 papers). Marylou Gabrié collaborates with scholars based in France, United States and Italy. Marylou Gabrié's co-authors include Florent Krza̧kała, Eric Vanden‐Eijnden, Grant M. Rotskoff, Andre Manoel, Lenka Zdeborová, Jean Barbier, Nicolas Macris, Eric W. Tramel, Francesco Caltagirone and Kaze W. K. Wong and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Chemical Theory and Computation and Physical Review X.

In The Last Decade

Co-authorship network of co-authors of Marylou Gabrié i

Fields of papers citing papers by Marylou Gabrié

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Marylou Gabrié

Since Specialization
Citations

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