Aurélien Bellet

7.0k citations
34 papers · 444 · h-index 13

Impact in

    • Speech Recognition and Synthesis
    • Privacy-Preserving Technologies in Data
    • Domain Adaptation and Few-Shot Learning
    • Machine Learning and Algorithms
    • Natural Language Processing Techniques
    • Speech and Audio Processing
    • Music and Audio Processing

Papers in

Aurélien Bellet

31 papers receiving 432 citations

Peers

Aurélien Bellet
Comparison fields: 5 of 79
  • Artificial Intelligence 291
  • Signal Processing 95
  • Computer Vision and Pattern Recognition 152
  • Statistics and Probability 13
  • Computer Science Applications 9
Replace Jianhua Chen with:
Jianhua Chen China
Krishna Kumar Sharma India
Qinliang Su China
Irina Matveeva United States
Dejiao Zhang United States
Mohamed Ishmael Belghazi Canada
Ming Xiang China
Oscar Li United States
Jiayi Wang China
Marthinus Christoffel du Plessis Japan
Aurélien Bellet relative to Jianhua Chen China Jianhua Chen's profile →
Citations per field
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Citations per year

Countries citing papers authored by Aurélien Bellet

Since Specialization
Citations

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

Fields of papers citing papers by Aurélien Bellet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Aurélien Bellet, 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 Aurélien Bellet Line = papers co-authored together Aurélien Bellet links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201452
2 201548
3 201447
4 201540
5 202034
6 201927
7 201226
8 202226
9 197225
10 202318
11 202217
12 201813
13 202012
14
Federated Multi-Task Learning under a Mixture of Distributions
202110
15 20119
16 20186
17
Distributed Frank-Wolfe Algorithm: A Unified Framework for Communication-Efficient Sparse Learning.
20144
18 20144
19 20224
20 20184

About Aurélien Bellet

Aurélien Bellet is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Management Science and Operations Research and Computational Mechanics, having authored 34 papers that have together received 444 indexed citations. Recurring topics across this work include Face and Expression Recognition (7 papers), Speech Recognition and Synthesis (7 papers), Topic Modeling (5 papers), Privacy-Preserving Technologies in Data (4 papers), Hate Speech and Cyberbullying Detection (3 papers), Data Quality and Management (3 papers), Sparse and Compressive Sensing Techniques (3 papers) and Stochastic Gradient Optimization Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (291 citations), Signal Processing (95 citations), Computer Vision and Pattern Recognition (152 citations), Statistics and Probability (13 citations) and Computer Science Applications (9 citations). Aurélien Bellet has collaborated with scholars based in France, United States and Switzerland. Frequent co-authors include Amaury Habrard, Marc Sebban, Emmanuel Vincent, Marc Tommasi, Brij Mohan Lal Srivastava, Fei Sha, Yuan Shi, Natalia Tomashenko, Kuan Liu and Xin Wang. Their work appears in journals such as Synthesis lectures on artificial intelligence and machine learning, Machine Learning, Neurocomputing, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies and Pattern Recognition.

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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