World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
12019
World Ranking
8185
National Ranking
185

Cédric Févotte publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Cédric Févotte sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 127 publications — 17th percentile

17% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Cédric Févotte D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Cédric Févotte sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 42 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Cédric Févotte is affiliated with the Toulouse Institute of Computer Science Research in France. Their research primarily focuses on computer science, with a significant emphasis on signal processing and related subfields.

The main fields of study associated with their work include:

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Computational Mechanics
  • Artificial Intelligence
  • Information Systems

The topics most frequently explored in their research are:

  • Sparse and Compressive Sensing Techniques
  • Music and Audio Processing
  • Face and Expression Recognition
  • Blind Source Separation Techniques
  • Speech and Audio Processing
  • Recommender Systems and Techniques
  • Optical measurement and interference techniques

Recent publications by Cédric Févotte include:

  • Phase Retrieval With Bregman Divergences and Application to Audio Signal Recovery, 2021, IEEE Journal of Selected Topics in Signal Processing
  • Neural content-aware collaborative filtering for cold-start music recommendation, 2022, Data Mining and Knowledge Discovery
  • Multi-resolution beta-divergence NMF for blind spectral unmixing, 2021, Signal Processing
  • Algorithms for audio inpainting based on probabilistic nonnegative matrix factorization, 2022, arXiv (Cornell University)
  • Negative Binomial Matrix Factorization, 2020, IEEE Signal Processing Letters

Their frequent coauthors in research collaborations include:

  • Paul Magron
  • Thomas Oberlin
  • Emmanuel Soubies
  • José Henrique de Morais Goulart
  • Pierre-Hugo Vial

Publications by Cédric Févotte are commonly found in these venues:

  • arXiv (Cornell University)
  • IEEE Signal Processing Letters
  • IEEE Transactions on Signal Processing
  • Signal Processing
  • HAL (Le Centre pour la Communication Scientifique Directe)

Best Publications

  • Performance measurement in blind audio source separation

    E. Vincent;R. Gribonval;C. Fevotte

  • Nonnegative matrix factorization with the itakura-saito divergence: With application to music analysis

    Cédric Févotte;Nancy Bertin;Jean-Louis Durrieu

  • Algorithms for nonnegative matrix factorization with the β-divergence

    Cédric Févotte;Jérôme Idier

  • Multichannel Nonnegative Matrix Factorization in Convolutive Mixtures for Audio Source Separation

    A. Ozerov;C. Fevotte

  • Algorithms for nonnegative matrix factorization with the beta-divergence

    Cédric Févotte;Jérôme Idier

  • Automatic Relevance Determination in Nonnegative Matrix Factorization with the $(eta)$-Divergence

    V. Y. F. Tan;C. Fevotte

  • BSS_EVAL Toolbox User Guide -- Revision 2.0

    Cédric Févotte;Rémi Gribonval;Emmanuel Vincent

  • Source/Filter Model for Unsupervised Main Melody Extraction From Polyphonic Audio Signals

    J.-L. Durrieu;G. Richard;B. David;C. Fevotte

  • Nonlinear Hyperspectral Unmixing With Robust Nonnegative Matrix Factorization

    Cedric Fevotte;Nicolas Dobigeon

  • A Bayesian Approach for Blind Separation of Sparse Sources

    C. Fevotte;S.J. Godsill

  • Static and Dynamic Source Separation Using Nonnegative Factorizations: A unified view

    Paris Smaragdis;Cedric Fevotte;Gautham J. Mysore;Nasser Mohammadiha

  • Alternating direction method of multipliers for non-negative matrix factorization with the beta-divergence

    Dennis L. Sun;Cédric Févotte

  • PROPOSALS FOR PERFORMANCE MEASUREMENT IN SOURCE SEPARATION

    Rémi Gribonval;Emmanuel Vincent;Cédric Févotte;Laurent Benaroya

  • Nonnegative matrix factorizations as probabilistic inference in composite models

    Cedric Fevotte;A. Taylan Cemgil

  • Multichannel nonnegative tensor factorization with structured constraints for user-guided audio source separation

    Alexey Ozerov;Cedric Fevotte;Raphael Blouet;Jean-Louis Durrieu

  • Two contributions to blind source separation using time-frequency distributions

    C. Fevotte;C. Doncarli

  • Factorial Scaled Hidden Markov Model for polyphonic audio representation and source separation

    Alexey Ozerov;Cedric Fevotte;Maurice Charbit

  • Blind separation of linear instantaneous mixtures of nonstationary surface myoelectric signals

    D. Farina;C. Fevotte;C. Doncarli;R. Merletti

  • Itakura-Saito nonnegative matrix factorization with group sparsity

    Augustin Lefevre;Francis Bach;Cedric Fevotte

  • Online algorithms for nonnegative matrix factorization with the Itakura-Saito divergence

    Augustin Lefevre;Francis Bach;Cedric Fevotte

  • Multichannel nonnegative matrix factorization in convolutive mixtures for audio source separation Factorisation en matrices à coefficients positifs de données multicanal convolutives pour la séparation de sources audio

    Alexey Ozerov;Cédric Févotte

Frequent Co-Authors

Simon J. Godsill
Simon J. Godsill University of Cambridge
Vincent Y. F. Tan
Vincent Y. F. Tan National University of Singapore
Emmanuel Vincent
Emmanuel Vincent University of Lorraine
Olivier Cappé
Olivier Cappé PSL University
Rémi Gribonval
Rémi Gribonval École Normale Supérieure de Lyon
Nicolas Dobigeon
Nicolas Dobigeon National Polytechnic Institute of Toulouse
Francis Bach
Francis Bach École Normale Supérieure
Paris Smaragdis
Paris Smaragdis University of Illinois at Urbana-Champaign
Frédéric Bimbot
Frédéric Bimbot French Institute for Research in Computer Science and Automation - INRIA
Fabian J. Theis
Fabian J. Theis Technical University of Munich

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