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Towards Interpretable Reinforcement Learning Using Attention Augmented Agents

Jun 06, 2019
Alex Mott, Daniel Zoran, Mike Chrzanowski, Daan Wierstra, Danilo J. Rezende


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Relational inductive biases, deep learning, and graph networks

Oct 17, 2018
Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinicius Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, Caglar Gulcehre, Francis Song, Andrew Ballard, Justin Gilmer, George Dahl, Ashish Vaswani, Kelsey Allen, Charles Nash, Victoria Langston, Chris Dyer, Nicolas Heess, Daan Wierstra, Pushmeet Kohli, Matt Botvinick, Oriol Vinyals, Yujia Li, Razvan Pascanu


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Learning to Search with MCTSnets

Jul 17, 2018
Arthur Guez, Théophane Weber, Ioannis Antonoglou, Karen Simonyan, Oriol Vinyals, Daan Wierstra, Rémi Munos, David Silver

* ICML 2018 (camera-ready version) 

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Relational recurrent neural networks

Jun 28, 2018
Adam Santoro, Ryan Faulkner, David Raposo, Jack Rae, Mike Chrzanowski, Theophane Weber, Daan Wierstra, Oriol Vinyals, Razvan Pascanu, Timothy Lillicrap


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Imagination-Augmented Agents for Deep Reinforcement Learning

Feb 14, 2018
Théophane Weber, Sébastien Racanière, David P. Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adria Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter Battaglia, Demis Hassabis, David Silver, Daan Wierstra


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Learning and Querying Fast Generative Models for Reinforcement Learning

Feb 08, 2018
Lars Buesing, Theophane Weber, Sebastien Racaniere, S. M. Ali Eslami, Danilo Rezende, David P. Reichert, Fabio Viola, Frederic Besse, Karol Gregor, Demis Hassabis, Daan Wierstra


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Matching Networks for One Shot Learning

Dec 29, 2017
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Koray Kavukcuoglu, Daan Wierstra


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Learning model-based planning from scratch

Jul 19, 2017
Razvan Pascanu, Yujia Li, Oriol Vinyals, Nicolas Heess, Lars Buesing, Sebastien Racanière, David Reichert, Théophane Weber, Daan Wierstra, Peter Battaglia


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Comparison of Maximum Likelihood and GAN-based training of Real NVPs

May 15, 2017
Ivo Danihelka, Balaji Lakshminarayanan, Benigno Uria, Daan Wierstra, Peter Dayan


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Recurrent Environment Simulators

Apr 19, 2017
Silvia Chiappa, Sébastien Racaniere, Daan Wierstra, Shakir Mohamed


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Neural Episodic Control

Mar 06, 2017
Alexander Pritzel, Benigno Uria, Sriram Srinivasan, Adrià Puigdomènech, Oriol Vinyals, Demis Hassabis, Daan Wierstra, Charles Blundell


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PathNet: Evolution Channels Gradient Descent in Super Neural Networks

Jan 30, 2017
Chrisantha Fernando, Dylan Banarse, Charles Blundell, Yori Zwols, David Ha, Andrei A. Rusu, Alexander Pritzel, Daan Wierstra


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Variational Intrinsic Control

Nov 22, 2016
Karol Gregor, Danilo Jimenez Rezende, Daan Wierstra

* 15 pages, 6 figures 

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Model-Free Episodic Control

Jun 14, 2016
Charles Blundell, Benigno Uria, Alexander Pritzel, Yazhe Li, Avraham Ruderman, Joel Z Leibo, Jack Rae, Daan Wierstra, Demis Hassabis


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Convolution by Evolution: Differentiable Pattern Producing Networks

Jun 08, 2016
Chrisantha Fernando, Dylan Banarse, Malcolm Reynolds, Frederic Besse, David Pfau, Max Jaderberg, Marc Lanctot, Daan Wierstra


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One-Shot Generalization in Deep Generative Models

May 25, 2016
Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka, Karol Gregor, Daan Wierstra

* 8pgs, 1pg references, 1pg appendix, In Proceedings of the 33rd International Conference on Machine Learning, JMLR: W&CP volume 48, 2016 

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One-shot Learning with Memory-Augmented Neural Networks

May 19, 2016
Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, Timothy Lillicrap

* 13 pages, 8 figures 

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Towards Conceptual Compression

Apr 29, 2016
Karol Gregor, Frederic Besse, Danilo Jimenez Rezende, Ivo Danihelka, Daan Wierstra

* 14 pages, 13 figures 

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Continuous control with deep reinforcement learning

Feb 29, 2016
Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, Daan Wierstra

* 10 pages + supplementary 

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Weight Uncertainty in Neural Networks

May 21, 2015
Charles Blundell, Julien Cornebise, Koray Kavukcuoglu, Daan Wierstra

* In Proceedings of the 32nd International Conference on Machine Learning (ICML 2015) 

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DRAW: A Recurrent Neural Network For Image Generation

May 20, 2015
Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, Daan Wierstra


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Stochastic Backpropagation and Approximate Inference in Deep Generative Models

May 30, 2014
Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra

* Appears In Proceedings of the 31st International Conference on Machine Learning (ICML), JMLR: W\&CP volume 32, 2014 

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Deep AutoRegressive Networks

May 20, 2014
Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra

* Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra. Deep AutoRegressive Networks. In Proceedings of the 31st International Conference on Machine Learning (ICML), JMLR: W&CP volume 32, 2014 
* Appears in Proceedings of the 31st International Conference on Machine Learning (ICML), Beijing, China, 2014 

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Playing Atari with Deep Reinforcement Learning

Dec 19, 2013
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, Martin Riedmiller

* NIPS Deep Learning Workshop 2013 

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Efficient Natural Evolution Strategies

Sep 26, 2012
Yi Sun, Daan Wierstra, Tom Schaul, Juergen Schmidhuber

* Puslished in GECCO'2009 

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Natural Evolution Strategies

Jun 22, 2011
Daan Wierstra, Tom Schaul, Tobias Glasmachers, Yi Sun, J√ľrgen Schmidhuber


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Evolino for recurrent support vector machines

Dec 15, 2005
Juergen Schmidhuber, Matteo Gagliolo, Daan Wierstra, Faustino Gomez

* 10 pages, 2 figures 

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