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D-Index & Metrics

Computer Science

D-Index
46
Citations
17435
World Ranking
6661
National Ranking
53

Christoph H. Lampert 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 Christoph H. Lampert 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: 144 publications — 24th percentile

24% of scientists in this discipline score the same or lower.

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

Christoph H. Lampert 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 Christoph H. Lampert 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: 46 D-Index — 53rd percentile

53% of scientists in this discipline score the same or lower.

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

Overview

Christoph H. Lampert is affiliated with the Institute of Science and Technology Austria in Austria. Their primary field of study is Computer Science, with a focus on several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Safety Research, and Computational Mechanics.

Their research spans multiple topics, particularly in areas such as Domain Adaptation and Few-Shot Learning, Adversarial Robustness in Machine Learning, Anomaly Detection Techniques and Applications, Machine Learning and Data Classification, Advanced Neural Network Applications, Privacy-Preserving Technologies in Data, and Advanced Vision and Imaging.

Christoph H. Lampert has an extensive publication record, with a significant number of papers published in various venues. Frequent publication outlets include:

  • arXiv (Cornell University)
  • Journal of Spatial Information Science
  • 2021 IEEE International Conference on Big Data (Big Data)
  • 2022 26th International Conference on Pattern Recognition (ICPR)
  • Enlighten: Publications (The University of Glasgow)

Notable recent papers authored or co-authored by Christoph H. Lampert include:

  • "Towards Understanding Knowledge Distillation" (2021, arXiv (Cornell University))
  • "Continual Learning: Applications and the Road Forward" (2023, arXiv (Cornell University))
  • "Object-Centric Image Generation with Factored Depths, Locations, and Appearances" (2020, arXiv (Cornell University))
  • "Overcoming Rare-Language Discrimination in Multi-Lingual Sentiment Analysis" (2021, 2021 IEEE International Conference on Big Data (Big Data))
  • "On the Sample Complexity of Adversarial Multi-Source PAC Learning" (2020, arXiv (Cornell University))

Frequent co-authors working with Christoph H. Lampert include:

  • Hossein Zakerinia
  • Bernd Prach
  • Paul Henderson
  • Nikola Konstantinov
  • Dan Alistarh

Best Publications

  • iCaRL: Incremental Classifier and Representation Learning

    Sylvestre-Alvise Rebuffi;Alexander Kolesnikov;Georg Sperl;Christoph H. Lampert

  • Learning to detect unseen object classes by between-class attribute transfer

    Christoph H Lampert;Hannes Nickisch;Stefan Harmeling

  • Attribute-Based Classification for Zero-Shot Visual Object Categorization

    Christoph H. Lampert;Hannes Nickisch;Stefan Harmeling

  • Zero-Shot Learning—A Comprehensive Evaluation of the Good, the Bad and the Ugly

    Yongqin Xian;Christoph H. Lampert;Bernt Schiele;Zeynep Akata

  • Beyond sliding windows: Object localization by efficient subwindow search

    C.H. Lampert;M.B. Blaschko;T. Hofmann

  • Seed, expand and constrain: Three principles for weakly-supervised image segmentation

    Alexander Kolesnikov;Christoph H. Lampert

  • Efficient Subwindow Search: A Branch and Bound Framework for Object Localization

    C.H. Lampert;M.B. Blaschko;T. Hofmann

  • Learning to Localize Objects with Structured Output Regression

    Matthew Blaschko;Christoph H Lampert

  • Structured Learning and Prediction in Computer Vision

    Sebastian Nowozin;Christoph H. Lampert

  • Correlational spectral clustering

    M.B. Blaschko;C.H. Lampert

  • Curriculum learning of multiple tasks

    Anastasia Pentina;Viktoriia Sharmanska;Christoph H. Lampert

  • Unsupervised Object Discovery: A Comparison

    Tinne Tuytelaars;Christoph H. Lampert;Matthew B. Blaschko;Wray Buntine

  • Learning to Rank Using Privileged Information

    Viktoriia Sharmanska;Novi Quadrianto;Christoph H. Lampert

  • Movement templates for learning of hitting and batting

    Jens Kober;Katharina Mulling;Oliver Kromer;Christoph H. Lampert

  • Distillation-Based Training for Multi-Exit Architectures

    Mary Phuong;Christoph Lampert

  • Document image dewarping using robust estimation of curled text lines

    A. Ulges;C.H. Lampert;T.M. Breuel

  • A PAC-Bayesian bound for Lifelong Learning

    Anastasia Pentina;Christoph Lampert

  • Kernel Methods in Computer Vision

    Christoph H. Lampert

  • Towards understanding knowledge distillation

    Mary Phuong;Christoph H. Lampert

  • Global connectivity potentials for random field models

    Sebastian Nowozin;Christoph H Lampert

  • Extrapolation and learning equations

    Georg Martius;Christoph H. Lampert

Frequent Co-Authors

Sebastian Nowozin
Sebastian Nowozin Microsoft (United States)
Thomas M. Breuel
Thomas M. Breuel Nvidia (United States)
Vittorio Ferrari
Vittorio Ferrari Google (United States)
Jan Peters
Jan Peters Technical University of Darmstadt
Vladimir Kolmogorov
Vladimir Kolmogorov Institute of Science and Technology Austria
Arthur Gretton
Arthur Gretton University College London
Andreas Bartels
Andreas Bartels Max Planck Society

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