Daan Wierstra
Daan Wierstra
Principal Scientist, DeepMind
Verifierad e-postadress på google.com
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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
92262015
Playing atari with deep reinforcement learning
V Mnih, K Kavukcuoglu, D Silver, A Graves, I Antonoglou, D Wierstra, ...
arXiv preprint arXiv:1312.5602, 2013
37112013
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
31392015
Stochastic backpropagation and approximate inference in deep generative models
DJ Rezende, S Mohamed, D Wierstra
arXiv preprint arXiv:1401.4082, 2014
23242014
Draw: A recurrent neural network for image generation
K Gregor, I Danihelka, A Graves, DJ Rezende, D Wierstra
arXiv preprint arXiv:1502.04623, 2015
12822015
Matching networks for one shot learning
O Vinyals, C Blundell, T Lillicrap, D Wierstra
Advances in neural information processing systems, 3630-3638, 2016
12712016
Deterministic policy gradient algorithms
D Silver, G Lever, N Heess, T Degris, D Wierstra, M Riedmiller
12132014
Weight uncertainty in neural networks
C Blundell, J Cornebise, K Kavukcuoglu, D Wierstra
arXiv preprint arXiv:1505.05424, 2015
8132015
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
5172016
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
4892018
PyBrain
T Schaul, J Bayer, D Wierstra, Y Sun, M Felder, F Sehnke, T RĆ¼ckstieĆ, ...
Journal of Machine Learning Research 11 (Feb), 743-746, 2010
3922010
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
2622017
One-shot learning with memory-augmented neural networks
A Santoro, S Bartunov, M Botvinick, D Wierstra, T Lillicrap
arXiv preprint arXiv:1605.06065, 2016
2582016
Imagination-augmented agents for deep reinforcement learning
S Racanière, T Weber, D Reichert, L Buesing, A Guez, DJ Rezende, ...
Advances in neural information processing systems, 5690-5701, 2017
2452017
Training recurrent networks by evolino
J Schmidhuber, D Wierstra, M Gagliolo, F Gomez
Neural computation 19 (3), 757-779, 2007
2422007
Natural evolution strategies
D Wierstra, T Schaul, J Peters, J Schmidhuber
2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on …, 2008
2262008
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
1882014
Deep autoregressive networks
K Gregor, I Danihelka, A Mnih, C Blundell, D Wierstra
arXiv preprint arXiv:1310.8499, 2013
1782013
Neural scene representation and rendering
SMA Eslami, DJ Rezende, F Besse, F Viola, AS Morcos, M Garnelo, ...
Science 360 (6394), 1204-1210, 2018
1732018
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
1722008
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Artiklar 1–20