World's Best Scientists 2026 revealed!
Aaron Courville

Aaron Courville

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Computer Science
Canada
2025

D-Index & Metrics

Computer Science

D-Index
95
Citations
183159
World Ranking
450
National Ranking
15

Aaron Courville 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 Aaron Courville 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: 254 publications — 64th percentile

64% of scientists in this discipline score the same or lower.

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

Aaron Courville 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 Aaron Courville 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: 95 D-Index — 97th percentile

97% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Computer Science in Canada Leader Award
  • 2023 - Research.com Computer Science in Canada Leader Award
  • 2022 - Research.com Computer Science in Canada Leader Award

Overview

Aaron Courville is affiliated with the University of Montreal in Canada, where they focus their research primarily in the field of Computer Science. Their work spans multiple subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Statistical and Nonlinear Physics, and Structural Biology.

Their research topics cover a broad range of themes such as Domain Adaptation and Few-Shot Learning, Reinforcement Learning in Robotics, Topic Modeling, Multimodal Machine Learning Applications, Generative Adversarial Networks and Image Synthesis, and Adversarial Robustness in Machine Learning.

Notable recent publications by Aaron Courville include:

  • Spirit In the Shell: A Mathematically Plausible Pathway from Emotions to Metacognition in Artificial Intelligence Systems, 2025, Zenodo (CERN European Organization for Nuclear Research)
  • Generative adversarial networks, 2020, Communications of the ACM
  • Static Analysis of Shape in TensorFlow Programs, 2020, arXiv (Cornell University)
  • Out-of-Distribution Generalization via Risk Extrapolation (REx), 2020, arXiv (Cornell University)
  • Data-Efficient Reinforcement Learning with Self-Predictive Representations, 2020, arXiv (Cornell University)

Aaron Courville frequently collaborates with several other researchers. Their frequent coauthors include:

  • Pablo Samuel Castro
  • Yoshua Bengio
  • Max Schwarzer
  • Johan Obando-Ceron
  • Alessandro Sordoni

Their work has been published extensively in various venues, with prominent publications appearing in:

  • arXiv (Cornell University)
  • Microscopy and Microanalysis
  • Communications of the ACM
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Journal of High Energy Physics

Best Publications

  • Generative Adversarial Nets

    Ian Goodfellow;Jean Pouget-Abadie;Mehdi Mirza;Bing Xu

  • Deep Learning

    Ian Goodfellow;Yoshua Bengio;Aaron Courville

  • Generative adversarial networks

    Ian Goodfellow;Jean Pouget-Abadie;Mehdi Mirza;Bing Xu

  • Representation Learning: A Review and New Perspectives

    Y. Bengio;A. Courville;P. Vincent

  • Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

    Kelvin Xu;Jimmy Ba;Ryan Kiros;Kyunghyun Cho

  • Improved training of wasserstein GANs

    Ishaan Gulrajani;Faruk Ahmed;Martin Arjovsky;Vincent Dumoulin

  • Brain tumor segmentation with Deep Neural Networks

    Mohammad Havaei;Axel Davy;David Warde-Farley;Antoine Biard

  • Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

    Kelvin Xu;Jimmy Ba;Ryan Kiros;Kyunghyun Cho

  • Why Does Unsupervised Pre-training Help Deep Learning?

    Dumitru Erhan;Aaron C. Courville;Yoshua Bengio;Pascal Vincent

  • Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

    Yoshua Bengio;Nicholas Léonard;Aaron C. Courville

  • Maxout Networks

    Ian Goodfellow;David Warde-Farley;Mehdi Mirza;Aaron Courville

  • Theano: A Python framework for fast computation of mathematical expressions

    Rami Al-Rfou;Guillaume Alain;Amjad Almahairi

  • Why Does Unsupervised Pre-training Help Deep Learning?

    Dumitru Erhan;Yoshua Bengio;Aaron Courville;Pierre-Antoine Manzagol

  • Building end-to-end dialogue systems using generative hierarchical neural network models

    Iulian V. Serban;Alessandro Sordoni;Yoshua Bengio;Aaron Courville

  • FiLM: Visual Reasoning with a General Conditioning Layer

    Ethan Perez;Ethan Perez;Florian Strub;Harm de Vries;Vincent Dumoulin

  • Challenges in Representation Learning: A Report on Three Machine Learning Contests

    Ian J. Goodfellow;Dumitru Erhan;Pierre Luc Carrier;Aaron Courville

  • Adversarially Learned Inference

    Vincent Dumoulin;Ishmael Belghazi;Ben Poole;Alex Lamb

  • An empirical evaluation of deep architectures on problems with many factors of variation

    Hugo Larochelle;Dumitru Erhan;Aaron Courville;James Bergstra

  • Describing Videos by Exploiting Temporal Structure

    Li Yao;Atousa Torabi;Kyunghyun Cho;Nicolas Ballas

  • Adversarially Learned Inference

    Vincent Dumoulin;Ishmael Belghazi;Ben Poole;Olivier Mastropietro

  • Challenges in representation learning

    Ian J. Goodfellow;Dumitru Erhan;Pierre Luc Carrier;Aaron Courville

Frequent Co-Authors

Yoshua Bengio
Yoshua Bengio University of Montreal
Chris Pal
Chris Pal Polytechnique Montréal
Ian Goodfellow
Ian Goodfellow Google (United States)
Nicolas Ballas
Nicolas Ballas Facebook (United States)
Hugo Larochelle
Hugo Larochelle Google (United States)
Joelle Pineau
Joelle Pineau McGill University
Pascal Vincent
Pascal Vincent Facebook (United States)
Kyunghyun Cho
Kyunghyun Cho New York University
Olivier Pietquin
Olivier Pietquin Google (United States)
Caglar Gulcehre
Caglar Gulcehre DeepMind (United Kingdom)

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