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As a Principal Scientist at DeepMind, Karén built and led the Large Scale Deep Learning team developing large AI models of real-world data. Karén played a key role in such AI breakthroughs as AlphaZero, AlphaFold, WaveNet, BigGAN, and Flamingo, to name a few.
Mar 19, 2024 · Karén Simonyan, Inflection’s co-founder, will join Microsoft as chief scientist for the new consumer AI group. In the past year, Nadella has been revamping his company’s major products around...
Jul 4, 2019 · Jeff Donahue, Karen Simonyan. Adversarially trained generative models (GANs) have recently achieved compelling image synthesis results. But despite early successes in using GANs for unsupervised representation learning, they have since been superseded by approaches based on self-supervision.
- Jeff Donahue, Karen Simonyan
- 2019
- Overview
- Results
- Models
- Acknowledgements
Convolutional networks (ConvNets) currently set the state of the art in visual recognition. The aim of this project is to investigate how the ConvNet depth affects their accuracy in the large-scale image recognition setting. Our main contribution is a rigorous evaluation of networks of increasing depth, which shows that a significant improvement on...
ImageNet Challenge The very deep ConvNets were the basis of our ImageNet ILSVRC-2014 submission, where our team (VGG) secured the first and the second places in the localisation and classificationtasks respectively. After the competition, we further improved our models, which has lead to the following ImageNet classification results: Generalisation...
We release our two best-performing models, with 16 and 19 weight layers (denoted as configurations D and E in the publication). The models are released under Creative Commons Attribution License. Please cite our technical report if you use the models. The models are compatible with the Caffe toolbox. They are available in the Caffe format from the ...
This work was supported by ERC grant VisRec no. 228180. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the GPUs used for this research.
Karen Simonyan. Building models that can be rapidly adapted to numerous tasks using only a handful of annotated examples is an open challenge for multimodal machine learning research. We...
Dec 23, 2020 · Here we present the MuZero algorithm, which, by combining a tree-based search with a learned model, achieves superhuman performance in a range of challenging and visually complex domains, without...
Karen Simonyan∗ & Andrew Zisserman+ Visual Geometry Group, Department of Engineering Science, University of Oxford {karen,az}@robots.ox.ac.uk ABSTRACT In this work we investigate the effect of the convolutional network depth on its accuracy in the large-scale image recognition setting. Ourmain contribution is
