François Bachoc
- Artificial Intelligence top 10%
- Computational Theory and Mathematics top 5%
- Statistics, Probability and Uncertainty top 2%
- Environmental Engineering top 10%
- Management Science and Operations Research top 5%
- Co-authors
- Nicolas DurrandeOlivier RoustantReinhard FurrerAgnès LagnouxJean‐Marc MartinezDéborah IdierDidier RullièreJérémy Rohmer
- Topics
- Gaussian Processes and Bayesian Inference (17 papers)Soil Geostatistics and Mapping (14 papers)Advanced Multi-Objective Optimization Algorithms (13 papers)
- Cited by
- Statistics, Probability and UncertaintyComputational Theory and MathematicsStatistics and Probability
- Journals
- SHILAP Revista de lepidopterologíaBiometrikaInformation Sciences
- Partner nations
- FranceSwitzerlandChile
In The Last Decade
François Bachoc
48 papers receiving 553 citations
Peers
Comparison fields: 5 of 84
- Artificial Intelligence 193
- Computational Theory and Mathematics 185
- Statistics, Probability and Uncertainty 146
- Environmental Engineering 106
- Management Science and Operations Research 91
Countries citing papers authored by François Bachoc
This map shows the geographic impact of François Bachoc'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 François Bachoc with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites François Bachoc more than expected).
Fields of papers citing papers by François Bachoc
This network shows the impact of papers produced by François Bachoc. 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 François Bachoc. The network helps show where François Bachoc may publish in the future.
Co-authorship network of co-authors of François Bachoc
This figure shows the co-authorship network connecting the top 25 collaborators of François Bachoc. A scholar is included among the top collaborators of François Bachoc 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 François Bachoc. François Bachoc is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 3 | |
| 7 | 2 | |
| 8 | 0 | |
| 9 | 15 | |
| 10 | 5 | |
| 11 | 4 | |
| 12 | 6 | |
| 13 | Sensitivity indices for independent groups of variables | 11 |
| 14 | 1 | |
| 15 | 12 | |
| 16 | 48 | |
| 17 | 20 | |
| 18 | 6 | |
| 19 | 2 | |
| 20 | 21 |
About François Bachoc
François Bachoc is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Environmental Engineering, having authored 53 papers that have together received 571 indexed citations. Recurring topics across this work include Gaussian Processes and Bayesian Inference (17 papers), Soil Geostatistics and Mapping (14 papers) and Advanced Multi-Objective Optimization Algorithms (13 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (146 citations), Computational Theory and Mathematics (185 citations) and Statistics and Probability (90 citations). François Bachoc has collaborated with scholars based in France, Switzerland and Chile. Frequent co-authors include Nicolas Durrande, Olivier Roustant, Reinhard Furrer, Agnès Lagnoux, Jean‐Marc Martinez, Déborah Idier, Didier Rullière, Jérémy Rohmer, Clément Chevalier and Julien Bect. Their work appears in journals such as SHILAP Revista de lepidopterología, Biometrika and Information Sciences.
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.