Publications (27)
Matching Networks for One Shot Learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap +2
Comparison of Maximum Likelihood and GAN-based training of Real NVPs
Ivo Danihelka, Balaji Lakshminarayanan, Benigno Uria +2
Learning model-based planning from scratch
Razvan Pascanu, Yujia Li, Oriol Vinyals +7
Model-Free Episodic Control
Charles Blundell, Benigno Uria, Alexander Pritzel +6
Recurrent Environment Simulators
Silvia Chiappa, Sébastien Racaniere, Daan Wierstra +1
Natural Evolution Strategies
Daan Wierstra, Tom Schaul, Tobias Glasmachers +2
Weight Uncertainty in Neural Networks
Charles Blundell, Julien Cornebise, Koray Kavukcuoglu +1
Stochastic Backpropagation and Approximate Inference in Deep Generative Models
Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra
Relational recurrent neural networks
Adam Santoro, Ryan Faulkner, David Raposo +7
One-shot Learning with Memory-Augmented Neural Networks
Adam Santoro, Sergey Bartunov, Matthew Botvinick +2
Evolino for recurrent support vector machines
Juergen Schmidhuber, Matteo Gagliolo, Daan Wierstra +1
One-Shot Generalization in Deep Generative Models
Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka +2
Convolution by Evolution: Differentiable Pattern Producing Networks
Chrisantha Fernando, Dylan Banarse, Malcolm Reynolds +5
Deep AutoRegressive Networks
Karol Gregor, Ivo Danihelka, Andriy Mnih +2
PathNet: Evolution Channels Gradient Descent in Super Neural Networks
Chrisantha Fernando, Dylan Banarse, Charles Blundell +5
Relational inductive biases, deep learning, and graph networks
Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst +24
Learning to Search with MCTSnets
Arthur Guez, Théophane Weber, Ioannis Antonoglou +5
Towards Conceptual Compression
Karol Gregor, Frederic Besse, Danilo Jimenez Rezende +2
Continuous control with deep reinforcement learning
Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel +5
DRAW: A Recurrent Neural Network For Image Generation
Karol Gregor, Ivo Danihelka, Alex Graves +2
Efficient Natural Evolution Strategies
Yi Sun, Daan Wierstra, Tom Schaul +1
Towards Interpretable Reinforcement Learning Using Attention Augmented Agents
Alex Mott, Daniel Zoran, Mike Chrzanowski +2
Imagination-Augmented Agents for Deep Reinforcement Learning
Théophane Weber, Sébastien Racanière, David P. Reichert +12
Neural Episodic Control
Alexander Pritzel, Benigno Uria, Sriram Srinivasan +5
Variational Intrinsic Control
Karol Gregor, Danilo Jimenez Rezende, Daan Wierstra
Learning and Querying Fast Generative Models for Reinforcement Learning
Lars Buesing, Theophane Weber, Sebastien Racaniere +8
Playing Atari with Deep Reinforcement Learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver +4