Jean-Patrick Baudry

727 citations
9 papers · 417 · h-index 6

Impact in

    • Statistical Methods and Inference
    • Statistical Methods and Bayesian Inference
    • Advanced Statistical Methods and Models
    • Statistical Distribution Estimation and Applications
    • Bayesian Methods and Mixture Models
    • Advanced Clustering Algorithms Research

Papers in

Jean-Patrick Baudry

9 papers receiving 405 citations

Peers

Jean-Patrick Baudry
Comparison fields: 5 of 111
  • Statistics and Probability 111
  • Artificial Intelligence 217
  • Signal Processing 44
  • Computational Mathematics 2
  • Statistics, Probability and Uncertainty 14
Replace Davide Pigoli with:
Davide Pigoli United Kingdom
Cathy Maugis France
Hien D. Nguyen Australia
Abhijit Dasgupta United States
Matthew A. Nunes United Kingdom
Poul Svante Eriksen Denmark
Adolfo J. Quiróz Venezuela
Vinayak Rao United States
Munmun Biswas Bangladesh
Juhyun Park United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by Jean-Patrick Baudry

Since Specialization
Citations

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

Fields of papers citing papers by Jean-Patrick Baudry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean-Patrick Baudry. 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 Jean-Patrick Baudry. The network helps show where Jean-Patrick Baudry may publish in the future.

Co-authors

The 9 scholars most cited alongside Jean-Patrick Baudry, 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 Jean-Patrick Baudry Line = papers co-authored together Jean-Patrick Baudry links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 2010222
2 2011101
3 201553
4 201522
5 201410
6
Sélection de modèle pour la classification non supervisée
20095
7 20212
8
Enhancing the selection of a model-based clustering with external categorical variables
20131
9
Enhancing The Selection Of A Number of Clusters in Model-Based Clustering with External Qualitative Variables
20131

About Jean-Patrick Baudry

Jean-Patrick Baudry is a scholar working on Artificial Intelligence, Statistics and Probability, Molecular Biology, Control and Systems Engineering and Signal Processing, having authored 9 papers that have together received 417 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (5 papers), Bayesian Methods and Mixture Models (5 papers), Statistical Methods and Inference (4 papers), Machine Learning and Algorithms (1 paper), Advanced Multi-Objective Optimization Algorithms (1 paper), Gene expression and cancer classification (1 paper), Data Management and Algorithms (1 paper) and Control Systems and Identification (1 paper). The work is most often cited by research in Statistics and Probability (111 citations), Artificial Intelligence (217 citations), Signal Processing (44 citations), Computational Mathematics (2 citations) and Statistics, Probability and Uncertainty (14 citations). Jean-Patrick Baudry has collaborated with scholars based in France, United States and Portugal. Frequent co-authors include Gilles Celeux, Raphaël Gottardo, Adrian E. Raftery, Kenneth Lo, Bertrand Michel, Cathy Maugis, Ana Sousa Ferreira, Margarida G. M. S. Cardoso and Olivier Wintenberger. Their work appears in journals such as Electronic Journal of Statistics, Statistics and Computing, Journal of Computational and Graphical Statistics, Advances in Data Analysis and Classification and OpenGrey (Institut de l'Information Scientifique et Technique).

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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