World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
17420
World Ranking
6996
National Ranking
91

Xavier Bresson 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 Xavier Bresson 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: 118 publications — 14th percentile

14% of scientists in this discipline score the same or lower.

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

Xavier Bresson 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 Xavier Bresson 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: 45 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Overview

Xavier Bresson is affiliated with the National University of Singapore in Singapore. Their research primarily focuses on computer science, with an emphasis on artificial intelligence and its applications in graph neural networks and related computational techniques.

The scientist has contributed extensively to the study of advanced graph neural networks, demonstrating interest and expertise in graph theory and algorithms as well as complex network analysis techniques. Their work also spans interdisciplinary topics such as machine learning in materials science, genomics and phylogenetic studies, and RNA and protein synthesis mechanisms.

Frequent co-authors collaborating with Xavier Bresson include Laurent Thomas, Vijay Prakash Dwivedi, Thomas Laurent, Yoshua Bengio, and Anh Tuan Luu. These collaborations underscore a network of researchers involved in similar artificial intelligence and computational fields.

Publication venues for their work are notable for a strong representation in:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • IEEE Transactions on Neural Networks and Learning Systems
  • Genome Research
  • bioRxiv (Cold Spring Harbor Laboratory)

Recent research papers authored or co-authored by Xavier Bresson include:

  • "A Generalization of Transformer Networks to Graphs" (2020), published in arXiv (Cornell University)
  • "Benchmarking Graph Neural Networks" (2020), published in arXiv (Cornell University)
  • "Multigraph Transformer for Free-Hand Sketch Recognition" (2021), published in IEEE Transactions on Neural Networks and Learning Systems
  • "Graph Neural Networks with Learnable Structural and Positional Representations" (2021), published in arXiv (Cornell University)
  • "The Transformer Network for the Traveling Salesman Problem" (2021), published in arXiv (Cornell University)

Best Publications

  • Convolutional neural networks on graphs with fast localized spectral filtering

    Michaël Defferrard;Xavier Bresson;Pierre Vandergheynst

  • Fast Global Minimization of the Active Contour/Snake Model

    Xavier Bresson;Selim Esedoglu;Pierre Vandergheynst;Jean-Philippe Thiran

  • Structured Sequence Modeling with Graph Convolutional Recurrent Networks

    Youngjoo Seo;Michaël Defferrard;Pierre Vandergheynst;Xavier Bresson

  • Bregmanized Nonlocal Regularization for Deconvolution and Sparse Reconstruction

    Xiaoqun Zhang;Martin Burger;Xavier Bresson;Stanley Osher

  • CayleyNets: Graph Convolutional Neural Networks With Complex Rational Spectral Filters

    Ron Levie;Federico Monti;Xavier Bresson;Michael M. Bronstein

  • Geometric Applications of the Split Bregman Method: Segmentation and Surface Reconstruction

    Tom Goldstein;Xavier Bresson;Stanley Osher

  • Fast dual minimization of the vectorial total variation norm and applications to color image processing

    Xavier Bresson;Tony F. Chan

  • Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks

    Federico Monti;Michael M. Bronstein;Xavier Bresson

  • Benchmarking Graph Neural Networks

    Vijay Prakash Dwivedi;Chaitanya K. Joshi;Thomas Laurent;Yoshua Bengio

  • A Generalization of Transformer Networks to Graphs

    Vijay Prakash Dwivedi;Xavier Bresson

  • Local Histogram Based Segmentation Using the Wasserstein Distance

    Kangyu Ni;Xavier Bresson;Tony Chan;Selim Esedoglu

  • Residual Gated Graph ConvNets

    Xavier Bresson;Thomas Laurent

  • FMA: A Dataset for Music Analysis.

    Michaël Defferrard;Kirell Benzi;Pierre Vandergheynst;Xavier Bresson

  • An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem

    Chaitanya K. Joshi;Thomas Laurent;Xavier Bresson

  • Completely Convex Formulation of the Chan-Vese Image Segmentation Model

    Ethan S. Brown;Tony F. Chan;Xavier Bresson

  • A Variational Model for Object Segmentation Using Boundary Information and Shape Prior Driven by the Mumford-Shah Functional

    Xavier Bresson;Pierre Vandergheynst;Jean-Philippe Thiran

  • Evaluation and Comparison of Current Fetal Ultrasound Image Segmentation Methods for Biometric Measurements: A Grand Challenge

    Sylvia Rueda;Sana Fathima;Caroline L. Knight;Mohammad Yaqub

  • Matrix Completion on Graphs

    Vassilis Kalofolias;Xavier Bresson;Michael M. Bronstein;Pierre Vandergheynst

  • An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization.

    Sébastien Tourbier;Xavier Bresson;Patric Hagmann;Jean-Philippe Thiran

  • Total variation and cheeger cuts

    Arthur Szlam;Xavier Bresson

Frequent Co-Authors

Jean-Philippe Thiran
Jean-Philippe Thiran École Polytechnique Fédérale de Lausanne
Pierre Vandergheynst
Pierre Vandergheynst École Polytechnique Fédérale de Lausanne
Michael M. Bronstein
Michael M. Bronstein University of Oxford
Patric Hagmann
Patric Hagmann University of Lausanne
Tony F. Chan
Tony F. Chan University of California, Los Angeles
Arthur Szlam
Arthur Szlam DeepMind (United Kingdom)
Stanley Osher
Stanley Osher University of California, Los Angeles
Sergiu Nedevschi
Sergiu Nedevschi Technical University of Cluj-Napoca
Reto Meuli
Reto Meuli University of Lausanne
Peng Xu
Peng Xu Chinese Academy of Sciences

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