Pierre Marquis

3.8k total citations
80 papers, 900 citations indexed

About

Pierre Marquis is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Networks and Communications. According to data from OpenAlex, Pierre Marquis has authored 80 papers receiving a total of 900 indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Artificial Intelligence, 20 papers in Computational Theory and Mathematics and 9 papers in Computer Networks and Communications. Recurrent topics in Pierre Marquis's work include Logic, Reasoning, and Knowledge (39 papers), Bayesian Modeling and Causal Inference (21 papers) and AI-based Problem Solving and Planning (15 papers). Pierre Marquis is often cited by papers focused on Logic, Reasoning, and Knowledge (39 papers), Bayesian Modeling and Causal Inference (21 papers) and AI-based Problem Solving and Planning (15 papers). Pierre Marquis collaborates with scholars based in France, Japan and Germany. Pierre Marquis's co-authors include Jérôme Lang, Sébastien Konieczny, Hélène Fargier, Paolo Liberatore, Sylvie Coste-Marquis, Jean-Marie Lagniez, Marion Delcroix, Ivan Berlin, Caroline Devred and Marie-Christine Lagasquie-Schiex and has published in prestigious journals such as Artificial Intelligence, Preventive Medicine and BJOG An International Journal of Obstetrics & Gynaecology.

In The Last Decade

Pierre Marquis

74 papers receiving 850 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Pierre Marquis France 15 621 174 146 84 79 80 900
Dingcheng Li United States 18 877 1.4× 88 0.5× 32 0.2× 4 0.0× 102 1.3× 69 1.3k
Shoji Hirano Japan 13 186 0.3× 138 0.8× 22 0.2× 10 0.1× 64 0.8× 112 553
Sunita Soni India 9 375 0.6× 31 0.2× 29 0.2× 20 0.2× 18 0.2× 25 727
Ian Dickinson United Kingdom 14 547 0.9× 11 0.1× 288 2.0× 23 0.3× 81 1.0× 36 974
Marina Velikova Netherlands 11 273 0.4× 51 0.3× 24 0.2× 7 0.1× 44 0.6× 28 468
Honghan Wu United Kingdom 18 528 0.9× 55 0.3× 26 0.2× 2 0.0× 62 0.8× 77 1.1k
R. Marı́n Spain 15 327 0.5× 58 0.3× 225 1.5× 2 0.0× 30 0.4× 63 620
Yuval Nardi Israel 9 147 0.2× 10 0.1× 36 0.2× 7 0.1× 20 0.3× 15 479
Rohit J. Kate United States 17 957 1.5× 28 0.2× 30 0.2× 3 0.0× 38 0.5× 37 1.4k

Countries citing papers authored by Pierre Marquis

Since Specialization
Citations

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

Fields of papers citing papers by Pierre Marquis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pierre Marquis

This figure shows the co-authorship network connecting the top 25 collaborators of Pierre Marquis. A scholar is included among the top collaborators of Pierre Marquis based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pierre Marquis. Pierre Marquis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Bottieau, Jérémie, et al.. (2024). Logic-based explanations of imbalance price forecasts using boosted trees. Electric Power Systems Research. 235. 110699–110699. 2 indexed citations
2.
Inoue, Katsumi, et al.. (2023). Editing Boolean Classifiers: A Belief Change Perspective. Proceedings of the AAAI Conference on Artificial Intelligence. 37(5). 6516–6524.
3.
Marquis, Pierre, et al.. (2022). On the Complexity of Enumerating Prime Implicants from Decision-DNNF Circuits. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 2583–2590. 2 indexed citations
4.
Konieczny, Sébastien, et al.. (2018). On Belief Promotion.. HAL (Le Centre pour la Communication Scientifique Directe). 297–307.
5.
Darwiche, Adnan, Pierre Marquis, Dan Suciu, & Stefan Szeider. (2018). Recent Trends in Knowledge Compilation (Dagstuhl Seminar 17381). DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 2 indexed citations
6.
Konieczny, Sébastien, et al.. (2015). Private Revision in a Multi-Agent Setting. Adaptive Agents and Multi-Agents Systems. 1677–1678. 1 indexed citations
7.
Fargier, Hélène & Pierre Marquis. (2014). Disjunctive closures for knowledge compilation. Artificial Intelligence. 216. 129–162. 4 indexed citations
8.
Konieczny, Sébastien, et al.. (2011). Belief Base Rationalization for Propositional Merging. HAL (Le Centre pour la Communication Scientifique Directe). 2 indexed citations
9.
Lang, Jérôme & Pierre Marquis. (2010). Reasoning under inconsistency: A forgetting-based approach. Artificial Intelligence. 174(12-13). 799–823. 28 indexed citations
10.
Coste-Marquis, Sylvie, Caroline Devred, Sébastien Konieczny, Marie-Christine Lagasquie-Schiex, & Pierre Marquis. (2007). On the merging of Dung's argumentation systems. Artificial Intelligence. 171(10-15). 730–753. 79 indexed citations
11.
Subtil, D., F Puech, P Lequien, et al.. (2003). Aspirin (100 mg) used for prevention of pre‐eclampsia in nulliparous women: the Essai Régional Aspirine Mère–Enfant study (Part 1). BJOG An International Journal of Obstetrics & Gynaecology. 110(5). 475–484. 72 indexed citations
12.
Lang, Jérôme & Pierre Marquis. (2000). In search of the right extension. Principles of Knowledge Representation and Reasoning. 31(1). 625–636. 6 indexed citations
13.
Bailleux, Olivier & Pierre Marquis. (1999). DISTANCE-SAT: complexity and algorithms. National Conference on Artificial Intelligence. 642–647. 10 indexed citations
14.
Amarenco, G., et al.. (1998). Qualité de vie des femmes souffrant d'impériosité mictionnelle avec ou sans fuites. Etude prospective après traitement par oxybutynine (1701 cas).. La Presse Médicale. 27(1). 5–10. 3 indexed citations
15.
Lang, Jérôme & Pierre Marquis. (1998). Complexity results for independence and definability in propositional logic. Principles of Knowledge Representation and Reasoning. 356–367. 11 indexed citations
16.
Lang, Jérôme & Pierre Marquis. (1998). Two forms of dependence in propositional logic: controllability and definability. National Conference on Artificial Intelligence. 268–273. 5 indexed citations
17.
Marquis, Pierre, et al.. (1996). A new algorithm for computing theory prime implicates compilations. National Conference on Artificial Intelligence. 504–509. 4 indexed citations
18.
Marquis, Pierre. (1995). Knowledge compilation using theory prime implicates. International Joint Conference on Artificial Intelligence. 837–843. 43 indexed citations
19.
Marquis, Pierre. (1994). Possible models approach via independency. European Conference on Artificial Intelligence. 336–340. 3 indexed citations
20.
Marquis, Pierre, et al.. (1990). Deductive/Abductvie diagnosis: the DA-principles. European Conference on Artificial Intelligence. 47–52. 1 indexed citations

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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