Thierry Denœux

11.8k total citations · 1 hit paper
180 papers, 6.6k citations indexed

About

Thierry Denœux is a scholar working on Artificial Intelligence, Management Science and Operations Research and Statistics and Probability. According to data from OpenAlex, Thierry Denœux has authored 180 papers receiving a total of 6.6k indexed citations (citations by other indexed papers that have themselves been cited), including 127 papers in Artificial Intelligence, 60 papers in Management Science and Operations Research and 35 papers in Statistics and Probability. Recurrent topics in Thierry Denœux's work include Multi-Criteria Decision Making (54 papers), Bayesian Modeling and Causal Inference (38 papers) and Neural Networks and Applications (29 papers). Thierry Denœux is often cited by papers focused on Multi-Criteria Decision Making (54 papers), Bayesian Modeling and Causal Inference (38 papers) and Neural Networks and Applications (29 papers). Thierry Denœux collaborates with scholars based in France, China and Thailand. Thierry Denœux's co-authors include Marie-Hélène Masson, Benjamin Quost, Su Ruan, Songsak Sriboonchitta, Régis Lengelle, Fahed Abdallah, Philippe Smets, Philippe Xu, Chunfeng Lian and Patrice Aknin and has published in prestigious journals such as Journal of Applied Physics, Applied Energy and IEEE Transactions on Image Processing.

In The Last Decade

Thierry Denœux

172 papers receiving 6.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A k-nearest neighbor classification rule based on Dempster-Shafer theory

1995 718 citations Thierry Denœux profile →

Peers

Thierry Denœux

AI

MSOR

CTM

CVPR

SP

Bo Yuan China

Rudolf Kruse Germany

Miin‐Shen Yang Taiwan

Edurne Barrenechea Spain

Shie Mannor Israel

Владик Крейнович United States

Philippe Smets Belgium

Etienne E. Kerre Belgium

Wen Jiang China

Abraham Kandel United States

Bo Yuan China

Thierry Denœux

2.4k ×0.6

AI

2.1k ×1.2

MSOR

1.2k ×1.0

CTM

481 ×0.4

CVPR

861 ×1.1

SP

Citations per year, relative to Thierry Denœux Thierry Denœux (= 1×) peers Bo Yuan

Countries citing papers authored by Thierry Denœux

Since Specialization

Citations

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

Fields of papers citing papers by Thierry Denœux

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thierry Denœux

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Su, Zhi‐gang, et al.. (2025). Multi-view evidential K-NN classification. Information Fusion. 120. 103113–103113.

2.

Huang, Ling, et al.. (2025). Evidential time-to-event prediction with calibrated uncertainty quantification. International Journal of Approximate Reasoning. 181. 109403–109403. 1 indexed citations

3.

Denœux, Thierry. (2024). Uncertainty Quantification in Regression Neural Networks Using Likelihood-Based Belief Functions. Lecture notes in computer science. 40–48. 1 indexed citations

4.

Lv, Ying, Bofeng Zhang, Xiaodong Yue, Thierry Denœux, & Yue Shan. (2024). Selecting reliable instances based on evidence theory for transfer learning. Expert Systems with Applications. 250. 123739–123739. 10 indexed citations

5.

Bouraoui, Zied, Antoine Cornuéjols, Thierry Denœux, et al.. (2024). Synergies between machine learning and reasoning - An introduction by the Kay R. Amel group. International Journal of Approximate Reasoning. 171. 109206–109206. 3 indexed citations

6.

Huang, Ling, Su Ruan, Pierre Decazes, & Thierry Denœux. (2024). Deep evidential fusion with uncertainty quantification and reliability learning for multimodal medical image segmentation. Information Fusion. 113. 102648–102648. 17 indexed citations

7.

Huang, Ling, Su Ruan, & Thierry Denœux. (2023). Semi-supervised multiple evidence fusion for brain tumor segmentation. Neurocomputing. 535. 40–52. 14 indexed citations

8.

Campagner, Andrea, Davide Ciucci, & Thierry Denœux. (2023). A distributional framework for evaluation, comparison and uncertainty quantification in soft clustering. International Journal of Approximate Reasoning. 162. 109008–109008. 4 indexed citations

9.

Kino, Hiori, Yasunobu Ando, Takashi Miyake, et al.. (2023). Evidence-based data mining method to reveal similarities between materials based on physical mechanisms. Journal of Applied Physics. 133(5). 1 indexed citations

10.

Denœux, Thierry. (2023). Belief Functions on the Real Line Defined by Transformed Gaussian Random Fuzzy Numbers. SPIRE - Sciences Po Institutional REpository. 1–6. 1 indexed citations

11.

Nagata, Takahiro, Toyohiro Chikyow, Hiori Kino, et al.. (2021). Evidence-based recommender system for high-entropy alloys. Nature Computational Science. 1(7). 470–478. 23 indexed citations

12.

Denœux, Thierry, et al.. (2016). Evidential clustering of large dissimilarity data. Knowledge-Based Systems. 106. 179–195. 58 indexed citations

13.

Lian, Chunfeng, Su Ruan, Thierry Denœux, Fabrice Jardin, & Pierre Véra. (2016). Selecting radiomic features from FDG-PET images for cancer treatment outcome prediction. Medical Image Analysis. 32. 257–268. 54 indexed citations

14.

Denœux, Thierry. (2011). Maximum likelihood estimation from fuzzy data using the EM algorithm. HAL (Le Centre pour la Communication Scientifique Directe). 3 indexed citations

15.

Denœux, Thierry, et al.. (2008). A New Justification of the Unnormalized Dempster's Rule of Combination from the Least Commitment Principle. The Florida AI Research Society. 666–671. 3 indexed citations

16.

Cherfaoui, Véronique, et al.. (2008). Distributed data fusion: application to confidence management in vehicular networks. International Conference on Information Fusion. 1–8. 9 indexed citations

17.

Abdallah, Fahed, et al.. (2008). Map matching algorithm using belief function theory. International Conference on Information Fusion. 1–8. 14 indexed citations

18.

Mercier, David, et al.. (2007). Fusion de décisions postales dans le cadre du Modèle des Croyances Transférables. DSpace (Centre National De La Recherche Scientifique). 24(2). 133–151. 1 indexed citations

19.

Denœux, Thierry, et al.. (1996). Urban Storm Water Pollution Forecasting Using Recurrent Neural Networks. 1 indexed citations

20.

Lengelle, Régis, et al.. (1995). Performance analysis of a MLP weight initialization algorithm.. The European Symposium on Artificial Neural Networks. 4 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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