Pascal Poupart

101 papers and 1.7k indexed citations i.

About

Pascal Poupart is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Pascal Poupart has authored 101 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 86 papers in Artificial Intelligence, 20 papers in Computer Vision and Pattern Recognition and 16 papers in Computational Theory and Mathematics. Recurrent topics in Pascal Poupart’s work include Bayesian Modeling and Causal Inference (27 papers), Reinforcement Learning in Robotics (23 papers) and Topic Modeling (21 papers). Pascal Poupart is often cited by papers focused on Bayesian Modeling and Causal Inference (27 papers), Reinforcement Learning in Robotics (23 papers) and Topic Modeling (21 papers). Pascal Poupart collaborates with scholars based in Canada, United States and China. Pascal Poupart's co-authors include Craig Boutilier, Jesse Hoey, Seyed Mehran Kazemi, Alex Mihailidis, Rishab Goel, Marcus A. Brubaker, Matthijs T. J. Spaan, Nikos Vlassis, Josep M. Porta and Dale Schuurmans and has published in prestigious journals such as Artificial Intelligence, IEEE Transactions on Cybernetics and Journal of Machine Learning Research.

In The Last Decade

Co-authorship network of co-authors of Pascal Poupart i

Fields of papers citing papers by Pascal Poupart

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Pascal Poupart

Since Specialization
Citations

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