Christophe Tribes

35 papers receiving 370 citations

Peers

Christophe Tribes
Comparison fields: 5 of 61
  • Computational Theory and Mathematics 150
  • Numerical Analysis 51
  • Statistics, Probability and Uncertainty 54
  • Computational Mechanics 70
  • Aerospace Engineering 82
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Countries citing papers authored by Christophe Tribes

Since Specialization
Citations

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

Fields of papers citing papers by Christophe Tribes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Christophe Tribes, 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 Christophe Tribes Line = papers co-authored together Christophe Tribes links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200643
2 199636
3 199835
4 202231
5 201430
6 201826
7 201525
8 200621
9 200520
10 202115
11 201515
12 201815
13 200412
14 201510
15
NOMAD User Guide. Version 3.7.2
20098
16 20148
17 20025
18 20135
19
HyperNOMAD: Hyperparameter optimization of deep neural networks using mesh adaptive direct search
20194
20 20134

About Christophe Tribes

Christophe Tribes is a scholar working on Computational Theory and Mathematics, Aerospace Engineering, Artificial Intelligence, Computational Mechanics and Numerical Analysis, having authored 40 papers that have together received 397 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (15 papers), Metaheuristic Optimization Algorithms Research (9 papers), Turbomachinery Performance and Optimization (9 papers), Advanced Optimization Algorithms Research (6 papers), Advanced Numerical Analysis Techniques (5 papers), Advanced Aircraft Design and Technologies (4 papers), Probabilistic and Robust Engineering Design (4 papers) and Computational Fluid Dynamics and Aerodynamics (4 papers). The work is most often cited by research in Computational Theory and Mathematics (150 citations), Numerical Analysis (51 citations), Statistics, Probability and Uncertainty (54 citations), Computational Mechanics (70 citations) and Aerospace Engineering (82 citations). Christophe Tribes has collaborated with scholars based in Canada, France and Australia. Frequent co-authors include Charles Audet, S. M. Sami, Jean‐Yves Trépanier, Sébastien Le Digabel, Dominique Pelletier, François Guibault, T. C. Vu, Jean‐François Dubé, Christophe Devals and N. Giammichele. Their work appears in journals such as Optimization and Engineering, ACM Transactions on Mathematical Software, Optimization Letters, Engineering Optimization and SIAM Journal on Optimization.

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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