Daan Wierstra
Daan Wierstra
Principal Scientist, DeepMind
Verified email at google.com
Title
Cited by
Cited by
Year
Human-level control through deep reinforcement learning
V Mnih, K Kavukcuoglu, D Silver, AA Rusu, J Veness, MG Bellemare, ...
nature 518 (7540), 529-533, 2015
141272015
Playing atari with deep reinforcement learning
V Mnih, K Kavukcuoglu, D Silver, A Graves, I Antonoglou, D Wierstra, ...
arXiv preprint arXiv:1312.5602, 2013
59172013
Continuous control with deep reinforcement learning
TP Lillicrap, JJ Hunt, A Pritzel, N Heess, T Erez, Y Tassa, D Silver, ...
arXiv preprint arXiv:1509.02971, 2015
55132015
Stochastic backpropagation and approximate inference in deep generative models
DJ Rezende, S Mohamed, D Wierstra
International conference on machine learning, 1278-1286, 2014
33892014
Matching networks for one shot learning
O Vinyals, C Blundell, T Lillicrap, K Kavukcuoglu, D Wierstra
arXiv preprint arXiv:1606.04080, 2016
26082016
Deterministic policy gradient algorithms
D Silver, G Lever, N Heess, T Degris, D Wierstra, M Riedmiller
International conference on machine learning, 387-395, 2014
19842014
Draw: A recurrent neural network for image generation
K Gregor, I Danihelka, A Graves, D Rezende, D Wierstra
International Conference on Machine Learning, 1462-1471, 2015
16252015
Weight uncertainty in neural network
C Blundell, J Cornebise, K Kavukcuoglu, D Wierstra
International Conference on Machine Learning, 1613-1622, 2015
14292015
Relational inductive biases, deep learning, and graph networks
PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ...
arXiv preprint arXiv:1806.01261, 2018
11292018
Meta-learning with memory-augmented neural networks
A Santoro, S Bartunov, M Botvinick, D Wierstra, T Lillicrap
International conference on machine learning, 1842-1850, 2016
9782016
PyBrain
T Schaul, J Bayer, D Wierstra, Y Sun, M Felder, F Sehnke, T Rückstieß, ...
Journal of Machine Learning Research 11 (ARTICLE), 743-746, 2010
4312010
Pathnet: Evolution channels gradient descent in super neural networks
C Fernando, D Banarse, C Blundell, Y Zwols, D Ha, AA Rusu, A Pritzel, ...
arXiv preprint arXiv:1701.08734, 2017
3922017
One-shot learning with memory-augmented neural networks
A Santoro, S Bartunov, M Botvinick, D Wierstra, T Lillicrap
arXiv preprint arXiv:1605.06065, 2016
3712016
Neural scene representation and rendering
SMA Eslami, DJ Rezende, F Besse, F Viola, AS Morcos, M Garnelo, ...
Science 360 (6394), 1204-1210, 2018
3092018
Natural evolution strategies
D Wierstra, T Schaul, J Peters, J Schmidhuber
2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on …, 2008
3022008
Natural evolution strategies
D Wierstra, T Schaul, T Glasmachers, Y Sun, J Peters, J Schmidhuber
The Journal of Machine Learning Research 15 (1), 949-980, 2014
2892014
Training recurrent networks by evolino
J Schmidhuber, D Wierstra, M Gagliolo, F Gomez
Neural computation 19 (3), 757-779, 2007
2762007
Deep autoregressive networks
K Gregor, I Danihelka, A Mnih, C Blundell, D Wierstra
International Conference on Machine Learning, 1242-1250, 2014
2312014
One-shot generalization in deep generative models
D Rezende, I Danihelka, K Gregor, D Wierstra
International Conference on Machine Learning, 1521-1529, 2016
2172016
A system for robotic heart surgery that learns to tie knots using recurrent neural networks
H Mayer, F Gomez, D Wierstra, I Nagy, A Knoll, J Schmidhuber
Advanced Robotics 22 (13-14), 1521-1537, 2008
2142008
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