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Daan Wierstra
Daan Wierstra
Principal Scientist, DeepMind
Zweryfikowany adres z google.com
Tytuł
Cytowane przez
Cytowane przez
Rok
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
291622015
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
152422015
Playing atari with deep reinforcement learning
V Mnih, K Kavukcuoglu, D Silver, A Graves, I Antonoglou, D Wierstra, ...
arXiv preprint arXiv:1312.5602, 2013
142092013
Matching networks for one shot learning
O Vinyals, C Blundell, T Lillicrap, D Wierstra
Advances in neural information processing systems 29, 2016
75542016
Stochastic backpropagation and approximate inference in deep generative models
DJ Rezende, S Mohamed, D Wierstra
International conference on machine learning, 1278-1286, 2014
56832014
Deterministic policy gradient algorithms
D Silver, G Lever, N Heess, T Degris, D Wierstra, M Riedmiller
International conference on machine learning, 387-395, 2014
47792014
Weight uncertainty in neural network
C Blundell, J Cornebise, K Kavukcuoglu, D Wierstra
International conference on machine learning, 1613-1622, 2015
37222015
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
33702018
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
28652016
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
24052015
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
10002014
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
9152017
Playing atari with deep reinforcement learning. arXiv 2013
V Mnih, K Kavukcuoglu, D Silver, A Graves, I Antonoglou, D Wierstra, ...
arXiv preprint arXiv:1312.5602, 2013
8952013
Neural scene representation and rendering
SMA Eslami, D Jimenez Rezende, F Besse, F Viola, AS Morcos, ...
Science 360 (6394), 1204-1210, 2018
6872018
Continuous control with deep reinforcement learning. arXiv 2015
TP Lillicrap, JJ Hunt, A Pritzel, N Heess, T Erez, Y Tassa, D Silver, ...
arXiv preprint arXiv:1509.02971, 1935
4801935
PyBrain
T Schaul, J Bayer, D Wierstra, Y Sun, M Felder, F Sehnke, T Rückstieß, ...
Journal of Machine Learning Research 11, 743-746, 2010
4612010
Imagination-augmented agents for deep reinforcement learning
S Racanière, T Weber, D Reichert, L Buesing, A Guez, ...
Advances in neural information processing systems 30, 2017
4422017
Variational intrinsic control
K Gregor, DJ Rezende, D Wierstra
arXiv preprint arXiv:1611.07507, 2016
4192016
Neural episodic control
A Pritzel, B Uria, S Srinivasan, AP Badia, O Vinyals, D Hassabis, ...
International conference on machine learning, 2827-2836, 2017
3892017
Deep autoregressive networks
K Gregor, I Danihelka, A Mnih, C Blundell, D Wierstra
International Conference on Machine Learning, 1242-1250, 2014
3212014
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