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Karen Simonyan
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*
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* Karen Simonyan
Karen Simonyan
,
a British computer scientist and researcher at
Google
DeepMind
, involved in the
WaveNet
speech synthesis system, and in the
AlphaGo Zero
and
AlphaZero
projects. He received his Ph.D. in
computer vision
from
Oxford University
in 2013
[1]
, and was one of the founders of
Vision Factory
, an Oxford University
spin-off
, where his aim was to improve
visual recognition systems
using
deep learning
.
Vision Factory
was acquired by Google DeepMind in October 2014
[2]
.
Karen Simonyan
[3]
Table of Contents
Selected Publications
2011 ...
2015 ...
External Links
References
What links here?
Selected Publications
[4]
[5]
2011 ...
Karen Simonyan
,
Andrew Zisserman
,
Antonio Criminisi
(
2011
).
Immediate Structured Visual Search for Medical Images
.
MICCAI 2011
,
pdf
Karen Simonyan
(
2013
).
Large-Scale Learning of Discriminative Image Representations
. Ph.D. thesis,
University of Oxford
, advisors
Andrew Zisserman
and
Antonio Criminisi
,
pdf
2015 ...
Guillaume Desjardins
,
Karen Simonyan
,
Razvan Pascanu
,
Koray Kavukcuoglu
(
2015
).
Natural Neural Networks
.
arXiv:1507.00210
Aäron van den Oord
,
Sander Dieleman
,
Heiga Zen
,
Karen Simonyan
,
Oriol Vinyals
,
Alex Graves
,
Nal Kalchbrenner
,
Andrew Senior
,
Koray Kavukcuoglu
(
2016
).
WaveNet: A Generative Model for Raw Audio
.
arXiv:1609.03499
[6]
David Silver
,
Julian Schrittwieser
,
Karen Simonyan
,
Ioannis Antonoglou
,
Aja Huang
,
Arthur Guez
,
Thomas Hubert
,
Lucas Baker
,
Matthew Lai
,
Adrian Bolton
,
Yutian Chen
,
Timothy Lillicrap
,
Fan Hui
,
Laurent Sifre
,
George van den Driessche
,
Thore Graepel
,
Demis Hassabis
(
2017
).
Mastering the game of Go without human knowledge
.
Nature
, Vol. 550
David Silver
,
Thomas Hubert
,
Julian Schrittwieser
,
Ioannis Antonoglou
,
Matthew Lai
,
Arthur Guez
,
Marc Lanctot
,
Laurent Sifre
,
Dharshan Kumaran
,
Thore Graepel
,
Timothy Lillicrap
,
Karen Simonyan
,
Demis Hassabis
(
2017
).
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
.
arXiv:1712.01815
»
AlphaZero
External Links
Karen Simonyan
Karen Simonyan - Google Scholar Citations
Karen Simonyan - Department of Engineering Science, University of Oxford - VideoLectures.NET
References
^
Karen Simonyan
(
2013
).
Large-Scale Learning of Discriminative Image Representations
. Ph.D. thesis,
University of Oxford
, advisors
Andrew Zisserman
and
Antonio Criminisi
^
Teaming up with Oxford University on Artificial Intelligence
by
Demis Hassabis
, Google Europe Blog, October 23, 2014
^
Image captured from
ICLR2015 "Very Deep Convolutional Networks for Large-Scale Image Recognition"
YouTube
Video, 0:39
^
dblp: Karen Simonyan
^
Karen Simonyan
^
WaveNet from Wikipedia
What links here?
Page
Date Edited
AlphaZero
Feb 10, 2018
Arthur Guez
Dec 6, 2017
Chess
Jan 21, 2018
David Silver
Feb 11, 2018
Deep Learning
Feb 12, 2018
DeepMind
Dec 9, 2017
Demis Hassabis
Dec 8, 2017
Dharshan Kumaran
Dec 9, 2017
Gian-Carlo Pascutto
Jan 16, 2018
Go
Jan 24, 2018
Ioannis Antonoglou
Dec 6, 2017
Julian Schrittwieser
Dec 7, 2017
Karen Simonyan
Dec 10, 2017
Koray Kavukcuoglu
Dec 10, 2017
Laurent Sifre
Dec 7, 2017
LCZero
Apr 18, 2018
Learning
Feb 20, 2018
Marc Lanctot
Jan 10, 2018
Mathematician
Apr 9, 2018
Matthew Lai
Dec 6, 2017
Monte-Carlo Tree Search
Apr 26, 2018
Neural Networks
Mar 12, 2018
People
Feb 28, 2018
Reinforcement Learning
Feb 12, 2018
Shih-Chieh Huang
Oct 18, 2017
Shogi
Feb 19, 2018
Thomas Hubert
Dec 7, 2017
Thore Graepel
Jan 10, 2018
Timothy Lillicrap
Dec 9, 2017
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a British computer scientist and researcher at Google DeepMind, involved in the WaveNet speech synthesis system, and in the AlphaGo Zero and AlphaZero projects. He received his Ph.D. in computer vision from Oxford University in 2013 [1], and was one of the founders of Vision Factory, an Oxford University spin-off, where his aim was to improve visual recognition systems using deep learning. Vision Factory was acquired by Google DeepMind in October 2014 [2].
Table of Contents
Selected Publications
[4] [5]2011 ...
2015 ...
External Links
References
What links here?
Up one level