Theophane Weber
Theophane Weber
Research Scientist at DeepMind
Verified email at - Homepage
TitleCited byYear
Imagination-augmented agents for deep reinforcement learning
T Weber, S Racanière, DP Reichert, L Buesing, A Guez, DJ Rezende, ...
arXiv preprint arXiv:1707.06203, 2017
Attend, infer, repeat: Fast scene understanding with generative models
SMA Eslami, N Heess, T Weber, Y Tassa, D Szepesvari, GE Hinton
Advances in Neural Information Processing Systems, 3225-3233, 2016
Gradient estimation using stochastic computation graphs
J Schulman, N Heess, T Weber, P Abbeel
Advances in Neural Information Processing Systems, 3528-3536, 2015
Neural scene representation and rendering
SMA Eslami, DJ Rezende, F Besse, F Viola, AS Morcos, M Garnelo, ...
Science 360 (6394), 1204-1210, 2018
Visual interaction networks: Learning a physics simulator from video
N Watters, D Zoran, T Weber, P Battaglia, R Pascanu, A Tacchetti
Advances in neural information processing systems, 4539-4547, 2017
Deep reinforcement learning in large discrete action spaces
G Dulac-Arnold, R Evans, H van Hasselt, P Sunehag, T Lillicrap, J Hunt, ...
arXiv preprint arXiv:1512.07679, 2015
Automated variational inference in probabilistic programming
D Wingate, T Weber
arXiv preprint arXiv:1301.1299, 2013
System linearization
T Weber, B Vigoda, P Pratt, J Park, M McCormick
US Patent App. 13/678,904, 2013
Learning model-based planning from scratch
R Pascanu, Y Li, O Vinyals, N Heess, L Buesing, S Racanière, D Reichert, ...
arXiv preprint arXiv:1707.06170, 2017
Learning and querying fast generative models for reinforcement learning
L Buesing, T Weber, S Racaniere, SM Eslami, D Rezende, DP Reichert, ...
arXiv preprint arXiv:1802.03006, 2018
Relational recurrent neural networks
A Santoro, R Faulkner, D Raposo, J Rae, M Chrzanowski, T Weber, ...
Advances in Neural Information Processing Systems, 7299-7310, 2018
Quantifying statistical interdependence by message passing on graphs—part II: multidimensional point processes
J Dauwels, F Vialatte, T Weber, T Musha, A Cichocki
Neural computation 21 (8), 2203-2268, 2009
Learning to search with MCTSnets
A Guez, T Weber, I Antonoglou, K Simonyan, O Vinyals, D Wierstra, ...
arXiv preprint arXiv:1802.04697, 2018
On similarity measures for spike trains
J Dauwels, F Vialatte, T Weber, A Cichocki
International Conference on Neural Information Processing, 177-185, 2008
Temporal difference variational auto-encoder
K Gregor, G Papamakarios, F Besse, L Buesing, T Weber
arXiv preprint arXiv:1806.03107, 2018
To wave or not to wave? Order release policies for warehouses with an automated sorter
J Gallien, T Weber
Manufacturing & Service Operations Management 12 (4), 642-662, 2010
Correlation decay in random decision networks
D Gamarnik, DA Goldberg, T Weber
Mathematics of Operations Research 39 (2), 229-261, 2013
Woulda, coulda, shoulda: Counterfactually-guided policy search
L Buesing, T Weber, Y Zwols, S Racaniere, A Guez, JB Lespiau, N Heess
arXiv preprint arXiv:1811.06272, 2018
Building machines that learn and think for themselves
M Botvinick, DGT Barrett, P Battaglia, N de Freitas, D Kumaran, JZ Leibo, ...
Behavioral and Brain Sciences 40, 2017
Reinforced variational inference
T Weber, N Heess, A Eslami, J Schulman, D Wingate, D Silver
Advances in Neural Information Processing Systems (NIPS) Workshops, 2015
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