World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
31
Citations
89438
World Ranking
13313
National Ranking
845

Overview

Jeff Donahue is affiliated with DeepMind in the United Kingdom and works within the field of computer science. Their research primarily spans several subfields, including computer vision and pattern recognition, artificial intelligence, signal processing, and statistical and nonlinear physics.

The scientist has contributed to various topics related to advanced computational methods. These topics include:

  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Advanced Image and Video Retrieval Techniques
  • Music and Audio Processing
  • Speech Recognition and Synthesis
  • Time Series Analysis and Forecasting
  • Generative Adversarial Networks and Image Synthesis

Jeff Donahue's publication record includes papers mainly published in the venue arXiv (Cornell University), accounting for three papers. Their recent papers include:

  • "Flamingo: a Visual Language Model for Few-Shot Learning" (2022), published in arXiv (Cornell University)
  • "End-to-End Adversarial Text-to-Speech" (2020), published in arXiv (Cornell University)
  • "Training Generative Adversarial Networks by Solving Ordinary Differential Equations" (2020), published in arXiv (Cornell University)

Their collaboration network features frequent co-authors such as Andrew Brock, Mikołaj Bińkowski, Karen Simonyan, Jean-Baptiste Alayrac, and Pauline Luc. These co-authors have multiple joint publications with Jeff Donahue, reflecting collaborative work mainly in their areas of research interest.

Best Publications

  • Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

    Ross Girshick;Jeff Donahue;Trevor Darrell;Jitendra Malik

  • Caffe: Convolutional Architecture for Fast Feature Embedding

    Yangqing Jia;Evan Shelhamer;Jeff Donahue;Sergey Karayev

  • Long-term recurrent convolutional networks for visual recognition and description

    Jeff Donahue;Lisa Anne Hendricks;Sergio Guadarrama;Marcus Rohrbach

  • Context Encoders: Feature Learning by Inpainting

    Deepak Pathak;Philipp Krahenbuhl;Jeff Donahue;Trevor Darrell

  • Large Scale GAN Training for High Fidelity Natural Image Synthesis

    Andrew Brock;Jeff Donahue;Karen Simonyan

  • DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

    Jeff Donahue;Yangqing Jia;Oriol Vinyals;Judy Hoffman

  • Region-Based Convolutional Networks for Accurate Object Detection and Segmentation

    Ross Girshick;Jeff Donahue;Trevor Darrell;Jitendra Malik

  • Long-Term Recurrent Convolutional Networks for Visual Recognition and Description

    Jeff Donahue;Lisa Anne Hendricks;Marcus Rohrbach;Subhashini Venugopalan

  • Sequence to Sequence -- Video to Text

    Subhashini Venugopalan;Marcus Rohrbach;Jeffrey Donahue;Raymond Mooney

  • Part-Based R-CNNs for Fine-Grained Category Detection

    Ning Zhang;Jeff Donahue;Ross B. Girshick;Trevor Darrell

  • Adversarial Feature Learning

    Jeff Donahue;Philipp Krähenbühl;Trevor Darrell

  • Translating Videos to Natural Language Using Deep Recurrent Neural Networks

    Subhashini Venugopalan;Huijuan Xu;Jeff Donahue;Marcus Rohrbach

  • Generating Visual Explanations

    Lisa Anne Hendricks;Zeynep Akata;Marcus Rohrbach;Marcus Rohrbach;Jeff Donahue

  • Large Scale Adversarial Representation Learning

    Jeff Donahue;Karen Simonyan

  • LSDA: Large Scale Detection through Adaptation

    Judy Hoffman;Sergio Guadarrama;Eric S Tzeng;Ronghang Hu

  • Efficient Learning of Domain-invariant Image Representations

    Judy Hoffman;Erik Rodner;Jeff Donahue;Trevor Darrell

  • Data-dependent Initializations of Convolutional Neural Networks

    Philipp Krähenbühl;Carl Doersch;Carl Doersch;Jeff Donahue;Trevor Darrell

  • Adversarial Video Generation on Complex Datasets

    Aidan Clark;Jeff Donahue;Karen Simonyan

  • Semi-supervised Domain Adaptation with Instance Constraints

    Jeff Donahue;Judy Hoffman;Erik Rodner;Kate Saenko

  • Visual Search at Pinterest

    Yushi Jing;David Liu;Dmitry Kislyuk;Andrew Zhai

  • High Fidelity Speech Synthesis with Adversarial Networks

    Mikołaj Bińkowski;Jeff Donahue;Sander Dieleman;Aidan Clark

Frequent Co-Authors

Trevor Darrell
Trevor Darrell University of California, Berkeley
Kate Saenko
Kate Saenko Boston University
Judy Hoffman
Judy Hoffman Georgia Institute of Technology
Karen Simonyan
Karen Simonyan DeepMind (United Kingdom)
Marcus Rohrbach
Marcus Rohrbach Facebook (United States)
Ross Girshick
Ross Girshick Facebook (United States)
Yangqing Jia
Yangqing Jia Alibaba Group (China)
Philipp Krähenbühl
Philipp Krähenbühl The University of Texas at Austin
Raymond J. Mooney
Raymond J. Mooney The University of Texas at Austin
Jitendra Malik
Jitendra Malik University of California, Berkeley

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