Pascal Poupart

6.0k citations
119 papers · 2.6k · h-index 26

Impact in

Papers in

Pascal Poupart

113 papers receiving 2.5k citations

Peers

Pascal Poupart
Comparison fields: 5 of 122
  • Artificial Intelligence 1.7k
  • Management Science and Operations Research 344
  • Computer Vision and Pattern Recognition 521
  • Computer Networks and Communications 391
  • Computational Theory and Mathematics 259
Replace Pier Luca Lanzi with:
Pier Luca Lanzi Italy
Longzhi Yang United Kingdom
Young-Koo Lee South Korea
Dongjin Song United States
Ran Gilad-Bachrach United States
Amedeo Cesta Italy
Philip Hingston Australia
Alois Ferscha Austria
Andrew L. Maas United States
Charles L. Isbell United States
Pascal Poupart relative to Pier Luca Lanzi Italy Pier Luca Lanzi's profile →
Citations per field
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Pier Luca Lanzi · 1×
Citations per year

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).

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.

Co-authors

The 25 scholars most cited alongside Pascal Poupart, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Pascal Poupart Line = papers co-authored together Pascal Poupart links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 119 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020202
2 2006160
3 2010144
4 2006138
5
Exploiting structure to efficiently solve large scale partially observable markov decision processes
2005131
6
Bounded Finite State Controllers
2003114
7 2006108
8 2005100
9 201385
10 200682
11
Bayesian reputation modeling in E-marketplaces sensitive to subjecthity, deception and change
200673
12
Factored partially observable Markov decision processes for dialogue management
200573
13 201671
14
Solving POMDPs with continuous or large discrete observation spaces
200567
15
Value-Directed Compression of POMDPs
200265
16 201860
17 201242
18 200942
19
VDCBPI: an Approximate Scalable Algorithm for Large POMDPs
200442
20 201537

About Pascal Poupart

Pascal Poupart is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Computer Networks and Communications and Management Science and Operations Research, having authored 119 papers that have together received 2.6k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (32 papers), Reinforcement Learning in Robotics (29 papers), Topic Modeling (22 papers), Machine Learning and Algorithms (19 papers), Natural Language Processing Techniques (13 papers), Formal Methods in Verification (12 papers), Speech and dialogue systems (8 papers) and Bayesian Methods and Mixture Models (8 papers). The work is most often cited by research in Artificial Intelligence (1.7k citations), Management Science and Operations Research (344 citations), Computer Vision and Pattern Recognition (521 citations), Computer Networks and Communications (391 citations) and Computational Theory and Mathematics (259 citations). Pascal Poupart has collaborated with scholars based in Canada, United States and China. Frequent co-authors include Craig Boutilier, Jesse Hoey, Nikos Vlassis, Alex Mihailidis, Kevin Regan, Rishab Goel, Seyed Mehran Kazemi, Marcus A. Brubaker, Josep M. Porta and Matthijs T. J. Spaan. Their work appears in journals such as International Journal of Approximate Reasoning, ACM Transactions on Interactive Intelligent Systems, Gerontology, Computer Vision and Image Understanding and Artificial Intelligence.

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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