Benjamin Quost

811 total citations
20 papers, 458 citations indexed

About

Benjamin Quost is a scholar working on Artificial Intelligence, Signal Processing and Computational Theory and Mathematics. According to data from OpenAlex, Benjamin Quost has authored 20 papers receiving a total of 458 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 6 papers in Signal Processing and 4 papers in Computational Theory and Mathematics. Recurrent topics in Benjamin Quost's work include Bayesian Modeling and Causal Inference (5 papers), Machine Learning and Algorithms (4 papers) and Multi-Criteria Decision Making (4 papers). Benjamin Quost is often cited by papers focused on Bayesian Modeling and Causal Inference (5 papers), Machine Learning and Algorithms (4 papers) and Multi-Criteria Decision Making (4 papers). Benjamin Quost collaborates with scholars based in France, Australia and Netherlands. Benjamin Quost's co-authors include Thierry Denœux, Marie-Hélène Masson, David Mercier, Jean-Daniel Chazot, Xun Wang, Sébastien Destercke, Jérôme Antoni, Jérôme Antoni, Shoumei Li and Vincent Frémont and has published in prestigious journals such as Expert Systems with Applications, Pattern Recognition and Journal of Sound and Vibration.

In The Last Decade

Benjamin Quost

15 papers receiving 444 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Benjamin Quost France 12 257 113 94 77 73 20 458
Hirotaka Hachiya Japan 14 332 1.3× 146 1.3× 39 0.4× 45 0.6× 47 0.6× 40 542
Hoai Minh Le France 12 138 0.5× 126 1.1× 43 0.5× 57 0.7× 29 0.4× 21 447
Chan-Cheng Liu Taiwan 12 350 1.4× 154 1.4× 30 0.3× 157 2.0× 67 0.9× 33 648
Geng Zhang China 11 117 0.5× 111 1.0× 33 0.4× 32 0.4× 19 0.3× 54 392
Lianmeng Jiao China 10 259 1.0× 71 0.6× 65 0.7× 81 1.1× 23 0.3× 39 382
Robert E. Banfield United States 8 323 1.3× 104 0.9× 15 0.2× 33 0.4× 49 0.7× 12 514
Anthony J. Pinar United States 11 128 0.5× 45 0.4× 90 1.0× 17 0.2× 19 0.3× 28 348
Jin Yu China 11 196 0.8× 295 2.6× 20 0.2× 21 0.3× 18 0.2× 21 512
Kumar S. Ray India 14 336 1.3× 326 2.9× 71 0.8× 93 1.2× 33 0.5× 73 778

Countries citing papers authored by Benjamin Quost

Since Specialization
Citations

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

Fields of papers citing papers by Benjamin Quost

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Benjamin Quost

This figure shows the co-authorship network connecting the top 25 collaborators of Benjamin Quost. A scholar is included among the top collaborators of Benjamin Quost 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 Benjamin Quost. Benjamin Quost 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.
Quost, Benjamin, et al.. (2025). Soft learning probabilistic circuits. International Journal of Approximate Reasoning. 185. 109467–109467.
2.
Trentesaux, Damien, et al.. (2024). Deep reinforcement learning with predictive auxiliary task for autonomous train collision avoidance. Journal of Rail Transport Planning & Management. 31. 100453–100453.
3.
Quost, Benjamin, et al.. (2024). Cautious classifier ensembles for set-valued decision-making. International Journal of Approximate Reasoning. 177. 109328–109328.
4.
Quost, Benjamin, et al.. (2023). Self Learning using Venn-Abers predictors. SPIRE - Sciences Po Institutional REpository.
5.
Quost, Benjamin, et al.. (2022). Cautious weighted random forests. Expert Systems with Applications. 213. 118883–118883. 11 indexed citations
6.
Quost, Benjamin, et al.. (2022). Vehicle consumption estimation via calibrated Gaussian Process regression. 2022 IEEE Intelligent Vehicles Symposium (IV). 30. 71–76.
7.
Masson, Marie-Hélène, Benjamin Quost, & Sébastien Destercke. (2019). Cautious relational clustering: A thresholding approach. Expert Systems with Applications. 139. 112837–112837. 4 indexed citations
8.
Quost, Benjamin, Thierry Denœux, & Shoumei Li. (2017). Parametric classification with soft labels using the evidential EM algorithm: linear discriminant analysis versus logistic regression. Advances in Data Analysis and Classification. 11(4). 659–690. 21 indexed citations
9.
Quost, Benjamin & Sébastien Destercke. (2017). Classification by pairwise coupling of imprecise probabilities. Pattern Recognition. 77. 412–425. 16 indexed citations
10.
Zhou, Dingfu, et al.. (2017). Moving object detection and segmentation in urban environments from a moving platform. Image and Vision Computing. 68. 76–87. 30 indexed citations
11.
Wang, Xun, Benjamin Quost, Jean-Daniel Chazot, & Jérôme Antoni. (2015). Iterative beamforming for identification of multiple broadband sound sources. Journal of Sound and Vibration. 365. 260–275. 31 indexed citations
12.
Quost, Benjamin, et al.. (2015). Estimating energy consumption of a PHEV using vehicle and on-board navigation data. 1. 755–760. 3 indexed citations
13.
Quost, Benjamin & Thierry Denœux. (2015). Clustering and classification of fuzzy data using the fuzzy EM algorithm. Fuzzy Sets and Systems. 286. 134–156. 26 indexed citations
14.
Wang, Xun, Benjamin Quost, Jean-Daniel Chazot, & Jérôme Antoni. (2015). Estimation of multiple sound sources with data and model uncertainties using the EM and evidential EM algorithms. Mechanical Systems and Signal Processing. 66-67. 159–177. 29 indexed citations
15.
Quost, Benjamin, et al.. (2013). CEVCLUS: evidential clustering with instance-level constraints for relational data. Soft Computing. 18(7). 1321–1335. 23 indexed citations
16.
Quost, Benjamin, Marie-Hélène Masson, & Thierry Denœux. (2010). Classifier fusion in the Dempster–Shafer framework using optimized t-norm based combination rules. International Journal of Approximate Reasoning. 52(3). 353–374. 85 indexed citations
17.
Quost, Benjamin, et al.. (2010). CECM: Constrained evidential -means algorithm. Computational Statistics & Data Analysis. 56(4). 894–914. 62 indexed citations
18.
Quost, Benjamin, Thierry Denœux, & Marie-Hélène Masson. (2006). Pairwise classifier combination using belief functions. Pattern Recognition Letters. 28(5). 644–653. 37 indexed citations
19.
Mercier, David, Benjamin Quost, & Thierry Denœux. (2006). Refined modeling of sensor reliability in the belief function framework using contextual discounting. Information Fusion. 9(2). 246–258. 78 indexed citations
20.
Quost, Benjamin, et al.. (2005). Pairwise classifier combination in the transferable belief model. 5. 8 pp.–8 pp.. 2 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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