World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
15386
World Ranking
5495
National Ranking
254

Ralf Herbrich 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 Ralf Herbrich 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: 131 publications — 19th percentile

19% of scientists in this discipline score the same or lower.

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

Ralf Herbrich 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 Ralf Herbrich 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: 50 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Overview

Ralf Herbrich is affiliated with the Hasso Plattner Institute in Germany. Their research primarily spans the field of Computer Science, with a dominant focus on Artificial Intelligence. Contributions also extend to Statistical and Nonlinear Physics, Transportation, Modeling and Simulation, and Epidemiology.

The main topics covered in Ralf Herbrich's work include:

  • Machine Learning and Algorithms
  • Neural Networks and Applications
  • Machine Learning and Data Classification
  • Complex Network Analysis Techniques
  • Opinion Dynamics and Social Influence
  • Human Mobility and Location-Based Analysis
  • COVID-19 epidemiological studies

Ralf Herbrich has published several recent papers, including:

  • "CRISP: A Probabilistic Model for Individual-Level COVID-19 Infection Risk Estimation Based on Contact Data," 2020, arXiv (Cornell University)
  • "De-Layering Social Networks by Shared Tastes of Friendships," 2021, Proceedings of the International AAAI Conference on Web and Social Media
  • "On the detrimental effect of invariances in the likelihood for variational inference," 2022, arXiv (Cornell University)
  • "Approximate Message Passing for Bayesian Neural Networks," 2025, arXiv (Cornell University)
  • "A PAC-Bayesian Analysis of Distance-Based Classifiers: Why Nearest-Neighbour works!," 2021, arXiv (Cornell University)

Frequent co-authors who have collaborated with Ralf Herbrich include:

  • Richard Kurle
  • Laura Dietz
  • Ben Gamari
  • John Guiver
  • Edward Snelson

Ralf Herbrich's publications frequently appear in the following venues:

  • arXiv (Cornell University)
  • Proceedings of the International AAAI Conference on Web and Social Media
  • Harvard Data Science Review

Best Publications

  • A Generalized Representer Theorem

    Bernhard Schölkopf;Bernhard Schölkopf;Ralf Herbrich;Ralf Herbrich;Alex J. Smola

  • Large margin rank boundaries for ordinal regression

    R. Herbrich

  • Practical Lessons from Predicting Clicks on Ads at Facebook

    Xinran He;Junfeng Pan;Ou Jin;Tianbing Xu

  • Learning Kernel Classifiers: Theory and Algorithms

    Ralf Herbrich

  • TrueSkill™: A Bayesian Skill Rating System

    Ralf Herbrich;Tom Minka;Thore Graepel

  • Learning Kernel Classifiers

    Ralf Herbrich

  • Fast Sparse Gaussian Process Methods: The Informative Vector Machine

    Ralf Herbrich;Neil D. Lawrence;Matthias Seeger

  • Web-Scale Bayesian Click-Through rate Prediction for Sponsored Search Advertising in Microsoft's Bing Search Engine

    Thore Graepel;Joaquin Q. Candela;Thomas Borchert;Ralf Herbrich

  • Support vector learning for ordinal regression

    R. Herbrich;T. Graepel;K. Obermayer

  • Kernel Methods for Measuring Independence

    Arthur Gretton;Ralf Herbrich;Alexander Smola;Olivier Bousquet

  • Matchbox: large scale online bayesian recommendations

    David H. Stern;Ralf Herbrich;Thore Graepel

  • Predicting Information Spreading in Twitter

    Tauhid R. Zaman;Ralf Herbrich;Jurgen Van Gael;David Stern

  • Bayes point machines

    Ralf Herbrich;Thore Graepel;Colin Campbell

  • Generalization Bounds for the Area Under the ROC Curve

    Shivani Agarwal;Thore Graepel;Ralf Herbrich;Sariel Har-Peled

  • Interactive interfaces for machine learning model evaluations

    Polly Po Yee Lee;Nicolle M. Correa;Leo Parker Dirac;Aleksandr Mikhaylovich Ingerman

  • Classification on Pairwise Proximity Data

    Thore Graepel;Ralf Herbrich;Peter Bollmann-Sdorra;Klaus Obermayer

  • The Perceptron Algorithm with Uneven Margins

    Yaoyong Li;Hugo Zaragoza;Ralf Herbrich;John Shawe-Taylor

  • Stereo video for gaming

    Thore K H Graepel;Andrew Blake;Ralf Herbrich

  • TrueSkill Through Time: Revisiting the History of Chess

    Pierre Dangauthier;Ralf Herbrich;Tom Minka;Thore Graepel

  • Learning Preference Relations for Information Retrieval

    Ralf Herbrich;Thore Graepel;Peter Bollmann-Sdorra;Klaus Obermayer

  • Classification on proximity data with LP-machines

    Thore Graepel;Ralf Herbrich;Bernhard Schölkopf;Alex Smola

  • Bayes Point Machines: Estimating the Bayes Point in Kernel Space

    R Herbrich;Th Graepel;Icg Campbell

Frequent Co-Authors

Thore Graepel
Thore Graepel University College London
Robert C. Williamson
Robert C. Williamson University of Tübingen
John Shawe-Taylor
John Shawe-Taylor University College London
Klaus Obermayer
Klaus Obermayer Technical University of Berlin
Yoram Bachrach
Yoram Bachrach DeepMind (United Kingdom)
Neil D. Lawrence
Neil D. Lawrence University of Cambridge
Matthias Seeger
Matthias Seeger Amazon (Germany)
Alexander J. Smola
Alexander J. Smola Amazon (United States)
Bernhard Schölkopf
Bernhard Schölkopf Max Planck Institute for Intelligent Systems
Tom Minka
Tom Minka Microsoft (United States)

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