Arnaud Joly

2.2k citations
16 papers · 153 · h-index 6

Impact in

    • Speech and Audio Processing
    • Music and Audio Processing
    • Speech Recognition and Synthesis
    • Topic Modeling
    • Natural Language Processing Techniques
    • Machine Learning and Data Classification
    • Speech and dialogue systems

Papers in

    • Music and Audio Processing 3
    • Speech and Audio Processing 2
    • Speech Recognition and Synthesis 7
    • Natural Language Processing Techniques 3
    • Topic Modeling 3
    • Speech and dialogue systems 2

Arnaud Joly

15 papers receiving 138 citations

Peers

Arnaud Joly
Comparison fields: 5 of 47
  • Signal Processing 46
  • Artificial Intelligence 102
  • Computer Vision and Pattern Recognition 21
  • Internal Medicine 3
  • Experimental and Cognitive Psychology 11
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Citations per year

Countries citing papers authored by Arnaud Joly

Since Specialization
Citations

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

Fields of papers citing papers by Arnaud Joly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 202049
2 201725
3 201419
4
L1-based compression of random forest models
201211
5 201710
6 20228
7 20226
8
Globally Induced Forest: A Prepruning Compression Scheme
20175
9 20194
10 20213
11 20213
12 20143
13 20173
14 20212
15 20241
16 20231

About Arnaud Joly

Arnaud Joly is a scholar working on Signal Processing, Artificial Intelligence, Cognitive Neuroscience, Computer Vision and Pattern Recognition and Management, Monitoring, Policy and Law, having authored 16 papers that have together received 153 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (7 papers), Natural Language Processing Techniques (3 papers), Music and Audio Processing (3 papers), Topic Modeling (3 papers), Speech and dialogue systems (2 papers), Speech and Audio Processing (2 papers), Functional Brain Connectivity Studies (2 papers) and Face and Expression Recognition (1 paper). The work is most often cited by research in Signal Processing (46 citations), Artificial Intelligence (102 citations), Computer Vision and Pattern Recognition (21 citations), Internal Medicine (3 citations) and Experimental and Cognitive Psychology (11 citations). Arnaud Joly has collaborated with scholars based in Belgium, France and United Kingdom. Frequent co-authors include Pierre Geurts, Alexis Moinet, Thomas Drugman, Louis A. Wehenkel, André Gothot, Cécile Oury, Nathalie Maes, Pierre Damas, Natacha Kadlub and Christelle Lecut. Their work appears in journals such as Intensive Care Medicine Experimental, Journal of Stomatology Oral and Maxillofacial Surgery, Archives de Pédiatrie, Lecture notes in computer science and ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

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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