World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
13227
World Ranking
10969
National Ranking
91

Patrik O. Hoyer 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 Patrik O. Hoyer 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: 84 publications — 4th percentile

4% of scientists in this discipline score the same or lower.

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

Patrik O. Hoyer 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 Patrik O. Hoyer 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: 36 D-Index — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Overview

Patrik O. Hoyer is affiliated with the University of Helsinki in Finland. Their research contributions are situated primarily within the field of Computer Science, with notable emphasis on subfields such as Artificial Intelligence and Signal Processing.

Their body of work addresses core topics including Bayesian Modeling and Causal Inference, Advanced Text Analysis Techniques, and Blind Source Separation Techniques. These areas reflect a focus on computational methods that involve statistical modeling, interpretation of complex text data, and extraction of independent signals from data mixtures.

Among Hoyer's recent publications is the paper titled DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model, published in 2021 in UNC Libraries. This work explores a methodological approach relevant to causal inference in linear non-Gaussian settings.

Frequent collaborators in their research include colleagues Shohei Shimizu, Takanori Inazumi, Yasuhiro Sogawa, Aapo Hyvärinen, and Yoshinobu Kawahara. These repeated collaborations indicate ongoing research projects likely focused on related themes in statistical and computational modeling.

  • DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model (2021, UNC Libraries)

  • Shohei Shimizu
  • Takanori Inazumi
  • Yasuhiro Sogawa
  • Aapo Hyvärinen
  • Yoshinobu Kawahara

  • UNC Libraries

  • Computer Science

  • Artificial Intelligence
  • Signal Processing

  • Bayesian Modeling and Causal Inference
  • Advanced Text Analysis Techniques
  • Blind Source Separation Techniques

Best Publications

  • Non-negative Matrix Factorization with Sparseness Constraints

    Patrik O. Hoyer

  • A Linear Non-Gaussian Acyclic Model for Causal Discovery

    Shohei Shimizu;Patrik O. Hoyer;Aapo Hyvärinen;Antti Kerminen

  • Non-negative sparse coding

    P.O. Hoyer

  • Nonlinear causal discovery with additive noise models

    Patrik O. Hoyer;Dominik Janzing;Joris M. Mooij;Jonas Peters

  • Emergence of Phase- and Shift-Invariant Features by Decomposition of Natural Images into Independent Feature Subspaces

    Aapo Hyvärinen;Patrik Hoyer

  • Topographic Independent Component Analysis

    Aapo Hyvärinen;Patrik O. Hoyer;Mika O. Inki

  • DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model

    Shohei Shimizu;Takanori Inazumi;Yasuhiro Sogawa;Aapo Hyvärinen

  • Independent component analysis applied to feature extraction from colour and stereo images.

    Patrik O Hoyer;Aapo Hyvärinen

  • A two-layer sparse coding model learns simple and complex cell receptive fields and topography from natural images

    Aapo Hyvärinen;Patrik O. Hoyer

  • Natural Image Statistics

    Aapo Hyvärinen;Jarmo Hurri;Patrik O. Hoyer

  • Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity

    Aapo Hyvärinen;Kun Zhang;Shohei Shimizu;Patrik O. Hoyer

  • Causal Inference by Independent Component Analysis: Theory and Applications*

    Alessio Moneta;Doris Entner;Patrik O. Hoyer;Alex Coad

  • Interpreting Neural Response Variability as Monte Carlo Sampling of the Posterior

    Patrik O. Hoyer;Aapo Hyvärinen

  • Estimation of causal effects using linear non-Gaussian causal models with hidden variables

    Patrik O. Hoyer;Shohei Shimizu;Antti J. Kerminen;Markus Palviainen

  • A multi-layer sparse coding network learns contour coding from natural images.

    Patrik O Hoyer;Aapo Hyvärinen

  • Modeling receptive fields with non-negative sparse coding

    Patrik O. Hoyer

  • Discovering cyclic causal models by independent components analysis

    Gustavo Lacerda;Peter Spirtes;Joseph Ramsey;Patrik O. Hoyer

  • Image feature extraction by sparse coding and independent component analysis

    A. Hyvarinen;E. Oja;P. Hoyer;J. Hurri

  • Learning linear cyclic causal models with latent variables

    Antti Hyttinen;Frederick Eberhardt;Patrik O. Hoyer

  • Causal modelling combining instantaneous and lagged effects: an identifiable model based on non-Gaussianity

    Aapo Hyvärinen;Shohei Shimizu;Patrik O. Hoyer

  • Experiment selection for causal discovery

    Antti Hyttinen;Frederick Eberhardt;Patrik O. Hoyer

  • Optimization Theory and Algorithms

    Aapo Hyvärinen;Jarmo Hurri;Patrik O. Hoyer

Frequent Co-Authors

Aapo Hyvärinen
Aapo Hyvärinen University of Helsinki
Peter Spirtes
Peter Spirtes Carnegie Mellon University
Dominik Janzing
Dominik Janzing Amazon (United States)
Erkki Oja
Erkki Oja Aalto University
Alex Coad
Alex Coad Waseda University
Joris M. Mooij
Joris M. Mooij University of Amsterdam
Richard Scheines
Richard Scheines Carnegie Mellon University
Kenneth A. Bollen
Kenneth A. Bollen University of North Carolina at Chapel Hill
Bernhard Schölkopf
Bernhard Schölkopf Max Planck Institute for Intelligent Systems
Jonas Peters
Jonas Peters ETH Zurich

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring additional educational pathways can enhance your experience as a computer science student in the USA. Many students consider related fields, and pursuing an online bachelor’s in electrical engineering is a popular option. This degree shares foundational skills with computer science and opens up careers in high-demand technology sectors.

If you’re seeking to boost your resume quickly, you may benefit from easy certifications to get online. These certifications can validate your skills in specific areas like programming, networking, or cybersecurity, and often lead to lucrative job opportunities without a long-term commitment.

For those interested in advancing their education efficiently, the quickest cheapest masters degree programs allow you to earn a valuable credential in less time and with lower tuition costs. This can accelerate your career growth and open doors to senior roles.

Finally, researching the most useful masters degrees highlights additional graduate programs in high demand across industries. Pursuing one of these degrees can help ensure strong long-term prospects in the evolving job market.

Best Scientists Citing Patrik O. Hoyer

Recently Published Articles