Pascal Poupart
Impact in
- Artificial Intelligence top 0.5%
- Reinforcement Learning in Robotics
- Bayesian Modeling and Causal Inference
- Machine Learning and Algorithms
- Topic Modeling
- Speech and dialogue systems
- Natural Language Processing Techniques
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- Context-Aware Activity Recognition Systems
Papers in ⓘ
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- Bayesian Modeling and Causal Inference 32
- Reinforcement Learning in Robotics 28
- Topic Modeling 21
- Machine Learning and Algorithms 18
- Natural Language Processing Techniques 13
- Bayesian Methods and Mixture Models 8
- Speech and dialogue systems 8
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- Formal Methods in Verification 12
- Co-authors
- Craig Boutilier (15 shared papers)Jesse Hoey (11 shared papers)Nikos Vlassis (3 shared papers)Alex Mihailidis (5 shared papers)Kevin Regan (3 shared papers)Josep M. Porta (1 shared paper)Matthijs T. J. Spaan (1 shared paper)Dale Schuurmans (5 shared papers)
- Journals
- International Journal of Approximate Reasoning (2 papers)Gerontology (1 paper)ACM Transactions on Interactive Intelligent Systems (1 paper)Artificial Intelligence (1 paper)IEEE Transactions on Neural Systems and Rehabilitation Engineering (1 paper)
- Partner nations
- CanadaUnited StatesChina
In The Last Decade
Pascal Poupart
111 papers receiving 2.2k citations
Peers
Comparison fields: 5 of 125
- Artificial Intelligence 1.5k
- Computer Vision and Pattern Recognition 484
- Management Science and Operations Research 280
- Physical Therapy, Sports Therapy and Rehabilitation 74
- Computer Networks and Communications 382
Countries citing papers authored by Pascal Poupart
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
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.
All Works
Showing the 20 most-cited of 117 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 160 | |
| 2 | 2010 | 143 | |
| 3 | 2006 | 137 | |
| 4 | Exploiting structure to efficiently solve large scale partially observable markov decision processes | 2005 | 130 |
| 5 | Bounded Finite State Controllers | 2003 | 114 |
| 6 | 2006 | 107 | |
| 7 | 2005 | 100 | |
| 8 | 2013 | 85 | |
| 9 | 2006 | 79 | |
| 10 | Bayesian reputation modeling in E-marketplaces sensitive to subjecthity, deception and change | 2006 | 73 |
| 11 | Factored partially observable Markov decision processes for dialogue management | 2005 | 71 |
| 12 | 2016 | 68 | |
| 13 | Solving POMDPs with continuous or large discrete observation spaces | 2005 | 67 |
| 14 | Value-Directed Compression of POMDPs | 2002 | 67 |
| 15 | 2018 | 59 | |
| 16 | VDCBPI: an Approximate Scalable Algorithm for Large POMDPs | 2004 | 42 |
| 17 | 2012 | 42 | |
| 18 | 2009 | 41 | |
| 19 | 2015 | 37 | |
| 20 | Model-based Bayesian reinforcement learning in partially observable domains | 2008 | 35 |
About Pascal Poupart
Pascal Poupart is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Management Science and Operations Research, Software and Computer Vision and Pattern Recognition, having authored 117 papers that have together received 2.4k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (32 papers), Reinforcement Learning in Robotics (28 papers), Topic Modeling (21 papers), Machine Learning and Algorithms (18 papers), Natural Language Processing Techniques (13 papers), Formal Methods in Verification (12 papers), Bayesian Methods and Mixture Models (8 papers) and Speech and dialogue systems (8 papers). The work is most often cited by research in Artificial Intelligence (1.5k citations), Computer Vision and Pattern Recognition (484 citations), Management Science and Operations Research (280 citations), Physical Therapy, Sports Therapy and Rehabilitation (74 citations) and Computer Networks and Communications (382 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, Josep M. Porta, Matthijs T. J. Spaan, Dale Schuurmans, Relu Patrascu and Jennifer Boger. Their work appears in journals such as International Journal of Approximate Reasoning, Gerontology, ACM Transactions on Interactive Intelligent Systems, Artificial Intelligence and IEEE Transactions on Neural Systems and Rehabilitation Engineering.
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.