Michel Mouchart

180 total papers · 1.5k total citations
72 papers, 789 citations indexed

About

Michel Mouchart is a scholar working on Artificial Intelligence, Statistics and Probability and Management Science and Operations Research. According to data from OpenAlex, Michel Mouchart has authored 72 papers receiving a total of 789 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 25 papers in Statistics and Probability and 11 papers in Management Science and Operations Research. Recurrent topics in Michel Mouchart's work include Bayesian Modeling and Causal Inference (15 papers), Advanced Statistical Methods and Models (15 papers) and Statistical Methods and Bayesian Inference (8 papers). Michel Mouchart is often cited by papers focused on Bayesian Modeling and Causal Inference (15 papers), Advanced Statistical Methods and Models (15 papers) and Statistical Methods and Bayesian Inference (8 papers). Michel Mouchart collaborates with scholars based in Belgium, United Kingdom and Italy. Michel Mouchart's co-authors include Jean‐Pierre Florens, Ernesto San Martı́n, Benoı̂t Flahaut, Isabelle Thomas, Federica Russo, Guillaume Wunsch, Jean‐Marie Rolin, Jean‐François Richard, Léopold Simar and Alejandro Jara and has published in prestigious journals such as SHILAP Revista de lepidopterología, Econometrica and Journal of Econometrics.

In The Last Decade

Michel Mouchart

65 papers receiving 710 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Michel Mouchart	225	197	167	107	106	72	789
Ana María Pérez Marín	84 0.4×	302 1.5×	97 0.6×	142 1.3×	75 0.7×	46	826
Catalina Bolancé	309 1.4×	258 1.3×	89 0.5×	36 0.3×	37 0.3×	67	859
Thomas S. Shively	266 1.2×	222 1.1×	114 0.7×	33 0.3×	19 0.2×	34	736
Xu Cheng	257 1.1×	216 1.1×	80 0.5×	120 1.1×	201 1.9×	61	902
Yoel Haitovsky	230 1.0×	315 1.6×	61 0.4×	23 0.2×	18 0.2×	35	840
Antonio Garcı́a-Ferrer	45 0.2×	258 1.3×	26 0.2×	124 1.2×	102 1.0×	39	670
John Deely	340 1.5×	95 0.5×	148 0.9×	97 0.9×	55 0.5×	53	824
L. I. Pettit	241 1.1×	92 0.5×	79 0.5×	54 0.5×	15 0.1×	26	823
Carla Rampichini	296 1.3×	134 0.7×	86 0.5×	20 0.2×	18 0.2×	42	763
David R. Bellhouse	301 1.3×	146 0.7×	138 0.8×	13 0.1×	25 0.2×	87	893

Countries citing papers authored by Michel Mouchart

Since Specialization

Citations

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

Fields of papers citing papers by Michel Mouchart

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michel Mouchart

This figure shows the co-authorship network connecting the top 25 collaborators of Michel Mouchart. A scholar is included among the top collaborators of Michel Mouchart 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 Michel Mouchart. Michel Mouchart is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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