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D-Index & Metrics

Computer Science

D-Index
55
Citations
203589
World Ranking
4167
National Ranking
253

Overview

Karen Simonyan is affiliated with DeepMind in the United Kingdom. Their research primarily lies in the domain of Computer Science, with a strong focus on Artificial Intelligence and related subfields.

The scientist has contributed to a significant number of publications, totaling 38 in Computer Science. Within this broad field, notable subfields include Artificial Intelligence with 22 publications, Computer Vision and Pattern Recognition with 11, Accounting with 10, Signal Processing with 5, and Atmospheric Science with 4 publications.

Simonyan's research covers several main topics. These include Corporate Finance and Governance, Natural Language Processing Techniques, Topic Modeling, Domain Adaptation and Few-Shot Learning, Private Equity and Venture Capital, Speech Recognition and Synthesis, and Advanced Neural Network Applications. Each of these topics is addressed in around six to ten publications, indicating a diverse and interdisciplinary research portfolio.

The scientist's frequent publication venues reflect their involvement in both journal and preprint platforms. The most common venue is arXiv (Cornell University), with 14 papers published. Other venues include Nature, with 2 publications, SSRN Electronic Journal with 2, as well as Entrepreneurship Theory and Practice and Journal of Business Venturing, each with one publication.

Among recent papers associated with their work are:

  • Improved protein structure prediction using potentials from deep learning, 2020, Nature
  • Flamingo: a Visual Language Model for Few-Shot Learning, 2022, arXiv (Cornell University)
  • Skilful precipitation nowcasting using deep generative models of radar, 2021, Nature
  • Training Compute-Optimal Large Language Models, 2022, arXiv (Cornell University)
  • Improving language models by retrieving from trillions of tokens, 2021, arXiv (Cornell University)

Collaboration is evident in Simonyan's work, with frequent coauthors including Aidan Clark, Oriol Vinyals, Erich Elsen, Laurent Sifre, and Simon Osindero. Each coauthor has collaborated on multiple occasions, with counts ranging from six to seven joint publications.

Best Publications

  • Very Deep Convolutional Networks for Large-Scale Image Recognition

    Karen Simonyan;Andrew Zisserman

  • Mastering the game of Go without human knowledge

    David Silver;Julian Schrittwieser;Karen Simonyan;Ioannis Antonoglou

  • Two-Stream Convolutional Networks for Action Recognition in Videos

    Karen Simonyan;Andrew Zisserman

  • Spatial transformer networks

    Max Jaderberg;Karen Simonyan;Andrew Zisserman;Koray Kavukcuoglu

  • Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

    Karen Simonyan;Andrea Vedaldi;Andrew Zisserman

  • Large Scale GAN Training for High Fidelity Natural Image Synthesis

    Andrew Brock;Jeff Donahue;Karen Simonyan

  • WaveNet: A Generative Model for Raw Audio

    Aäron van den Oord;Sander Dieleman;Heiga Zen;Karen Simonyan

  • Return of the Devil in the Details: Delving Deep into Convolutional Nets

    Ken Chatfield;Karen Simonyan;Andrea Vedaldi;Andrew Zisserman

  • A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play.

    David Silver;Thomas Hubert;Julian Schrittwieser;Ioannis Antonoglou

  • Improved protein structure prediction using potentials from deep learning

    Andrew W. Senior;Richard Evans;John Jumper;James Kirkpatrick

  • DARTS: Differentiable Architecture Search

    Hanxiao Liu;Karen Simonyan;Yiming Yang

  • The Kinetics Human Action Video Dataset

    Andrew Zisserman;Joao Carreira;Karen Simonyan;Will Kay

  • Mastering Atari, Go, chess and shogi by planning with a learned model

    Julian Schrittwieser;Ioannis Antonoglou;Thomas Hubert;Karen Simonyan

  • Training Compute-Optimal Large Language Models

    Unknown

  • Reading Text in the Wild with Convolutional Neural Networks

    Max Jaderberg;Karen Simonyan;Andrea Vedaldi;Andrew Zisserman

  • Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

    David Silver;Thomas Hubert;Julian Schrittwieser;Ioannis Antonoglou

  • Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition

    Max Jaderberg;Karen Simonyan;Andrea Vedaldi;Andrew Zisserman

  • StarCraft II: A New Challenge for Reinforcement Learning

    Oriol Vinyals;Timo Ewalds;Sergey Bartunov;Petko Georgiev

  • IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures

    Lasse Espeholt;Hubert Soyer;Remi Munos;Karen Simonyan

  • Skilful precipitation nowcasting using deep generative models of radar.

    Suman V. Ravuri;Karel Lenc;Matthew Willson;Dmitry Kangin;Dmitry Kangin

  • Hierarchical Representations for Efficient Architecture Search

    Hanxiao Liu;Karen Simonyan;Oriol Vinyals;Chrisantha Fernando

Frequent Co-Authors

Andrew Zisserman
Andrew Zisserman University of Oxford
Koray Kavukcuoglu
Koray Kavukcuoglu DeepMind (United Kingdom)
Oriol Vinyals
Oriol Vinyals DeepMind (United Kingdom)
Aaron van den Oord
Aaron van den Oord Google (United States)
Andrea Vedaldi
Andrea Vedaldi University of Oxford
Jeff Donahue
Jeff Donahue DeepMind (United Kingdom)
Alex Graves
Alex Graves Google (United States)
Demis Hassabis
Demis Hassabis Google (United States)
David Silver
David Silver DeepMind (United Kingdom)
Timothy P. Lillicrap
Timothy P. Lillicrap University College London

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