Daan Wierstra

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 33

Top Topics

Image Generation

Policy Gradient

Top Venues

Publications

SIMA Team, Maria Abi Raad, Arun Ahuja, Catarina Barros, Frederic Besse, Andrew Bolt, Adrian Bolton, Bethanie Brownfield, Gavin Buttimore, Max Cant, Sarah Chakera, Stephanie C. Y. Chan, Jeff Clune, Adrian Collister, Vikki Copeman, Alex Cullum, Ishita Dasgupta, Dario de Cesare, Julia Di Trapani, Yani Donchev, Emma Dunleavy, Martin Engelcke, Ryan Faulkner, Frankie Garcia, Charles Gbadamosi, Zhitao Gong, Lucy Gonzalez, Kshitij Gupta, Karol Gregor, Arne Olav Hallingstad, Tim Harley, Sam Haves, Felix Hill, Ed Hirst, Drew A. Hudson, Jony Hudson, Steph Hughes-Fitt, Danilo J. Rezende, Mimi Jasarevic, Laura Kampis, Nan Rosemary Ke, Thomas Keck, Junkyung Kim, Oscar Knagg, Kavya Kopparapu, Andrew K. Lampinen, Shane Legg, Alexander Lerchner, Marjorie Limont, Yulan Liu, Maria Loks-Thompson, Joseph Marino, Kathryn Martin Cussons, Loic Matthey, Siobhan Mcloughlin, Piermaria Mendolicchio, Hamza Merzic, Anna Mitenkova, Alexandre Moufarek, Valéria Oliveira, Yanko Gitahy Oliveira, Hannah Openshaw, Renke Pan, Aneesh Pappu, Alex Platonov, Ollie Purkiss, David P. Reichert, John Reid, Pierre Harvey Richemond, Tyson Roberts, Giles Ruscoe, Jaume Sanchez Elias, Tasha Sandars, Daniel P. Sawyer, Tim Scholtes, Guy Simmons, Daniel Slater, Hubert Soyer, Heiko Strathmann, Peter Stys, Allison C. Tam, Denis Teplyashin, Tayfun Terzi, Davide Vercelli, Bojan Vujatovic, Marcus Wainwright, Jane X. Wang, Zhengdong Wang, Daan Wierstra, Duncan Williams, Nathaniel Wong, Sarah York, Nick Young
Scaling Instructable Agents Across Many Simulated Worlds. CoRR (2024)
Alex Mott, Daniel Zoran, Mike Chrzanowski, Daan Wierstra, Danilo J. Rezende
Towards Interpretable Reinforcement Learning Using Attention Augmented Agents. CoRR (2019)
Alexander Mott, Daniel Zoran, Mike Chrzanowski, Daan Wierstra, Danilo Jimenez Rezende
Towards Interpretable Reinforcement Learning Using Attention Augmented Agents. NeurIPS (2019)
Adam Santoro, Ryan Faulkner, David Raposo, Jack W. Rae, Mike Chrzanowski, Theophane Weber, Daan Wierstra, Oriol Vinyals, Razvan Pascanu, Timothy P. Lillicrap
Relational recurrent neural networks. CoRR (2018)
Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinícius Flores Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, Çaglar Gülçehre, H. Francis Song, Andrew J. Ballard, Justin Gilmer, George E. Dahl, Ashish Vaswani, Kelsey R. Allen, Charles Nash, Victoria Langston, Chris Dyer, Nicolas Heess, Daan Wierstra, Pushmeet Kohli, Matthew Botvinick, Oriol Vinyals, Yujia Li, Razvan Pascanu
Relational inductive biases, deep learning, and graph networks. CoRR (2018)
Lars Buesing, Theophane Weber, Sébastien Racanière, S. M. Ali Eslami, Danilo Jimenez Rezende, David P. Reichert, Fabio Viola, Frederic Besse, Karol Gregor, Demis Hassabis, Daan Wierstra
Learning and Querying Fast Generative Models for Reinforcement Learning. CoRR (2018)
Arthur Guez, Theophane Weber, Ioannis Antonoglou, Karen Simonyan, Oriol Vinyals, Daan Wierstra, Rémi Munos, David Silver
Learning to Search with MCTSnets. ICML (2018)
Arthur Guez, Théophane Weber, Ioannis Antonoglou, Karen Simonyan, Oriol Vinyals, Daan Wierstra, Rémi Munos, David Silver
Learning to Search with MCTSnets. CoRR (2018)
Adam Santoro, Ryan Faulkner, David Raposo, Jack W. Rae, Mike Chrzanowski, Theophane Weber, Daan Wierstra, Oriol Vinyals, Razvan Pascanu, Timothy P. Lillicrap
Relational recurrent neural networks. NeurIPS (2018)
Sébastien Racanière, Theophane Weber, David P. Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter W. Battaglia, Demis Hassabis, David Silver, Daan Wierstra
Imagination-Augmented Agents for Deep Reinforcement Learning. NIPS (2017)
Silvia Chiappa, Sébastien Racanière, Daan Wierstra, Shakir Mohamed
Recurrent Environment Simulators. CoRR (2017)
Theophane Weber, Sébastien Racanière, David P. Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter W. Battaglia, David Silver, Daan Wierstra
Imagination-Augmented Agents for Deep Reinforcement Learning. CoRR (2017)
Alexander Pritzel, Benigno Uria, Sriram Srinivasan, Adrià Puigdomènech Badia, Oriol Vinyals, Demis Hassabis, Daan Wierstra, Charles Blundell
Neural Episodic Control. CoRR (2017)
Karol Gregor, Danilo Jimenez Rezende, Daan Wierstra
Variational Intrinsic Control. ICLR (Workshop) (2017)
Razvan Pascanu, Yujia Li, Oriol Vinyals, Nicolas Heess, Lars Buesing, Sébastien Racanière, David P. Reichert, Theophane Weber, Daan Wierstra, Peter W. Battaglia
Learning model-based planning from scratch. CoRR (2017)
Matthew Botvinick, David G. T. Barrett, Peter W. Battaglia, Nando de Freitas, Dharshan Kumaran, Joel Z. Leibo, Tim Lillicrap, Joseph Modayil, S. Mohamed, Neil C. Rabinowitz, Danilo Jimenez Rezende, Adam Santoro, Tom Schaul, Christopher Summerfield, Greg Wayne, Theophane Weber, Daan Wierstra, Shane Legg, Demis Hassabis
Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017. CoRR (2017)
Ivo Danihelka, Balaji Lakshminarayanan, Benigno Uria, Daan Wierstra, Peter Dayan
Comparison of Maximum Likelihood and GAN-based training of Real NVPs. CoRR (2017)
Silvia Chiappa, Sébastien Racanière, Daan Wierstra, Shakir Mohamed
Recurrent Environment Simulators. ICLR (Poster) (2017)
Chrisantha Fernando, Dylan Banarse, Charles Blundell, Yori Zwols, David Ha, Andrei A. Rusu, Alexander Pritzel, Daan Wierstra
PathNet: Evolution Channels Gradient Descent in Super Neural Networks. CoRR (2017)
Alexander Pritzel, Benigno Uria, Sriram Srinivasan, Adrià Puigdomènech Badia, Oriol Vinyals, Demis Hassabis, Daan Wierstra, Charles Blundell
Neural Episodic Control. ICML (2017)
Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka, Karol Gregor, Daan Wierstra
One-Shot Generalization in Deep Generative Models. ICML (2016)
Karol Gregor, Frederic Besse, Danilo Jimenez Rezende, Ivo Danihelka, Daan Wierstra
Towards Conceptual Compression. CoRR (2016)
Oriol Vinyals, Charles Blundell, Timothy P. Lillicrap, Koray Kavukcuoglu, Daan Wierstra
Matching Networks for One Shot Learning. CoRR (2016)
Karol Gregor, Danilo Jimenez Rezende, Daan Wierstra
Variational Intrinsic Control. CoRR (2016)
Charles Blundell, Benigno Uria, Alexander Pritzel, Yazhe Li, Avraham Ruderman, Joel Z. Leibo, Jack W. Rae, Daan Wierstra, Demis Hassabis
Model-Free Episodic Control. CoRR (2016)
Oriol Vinyals, Charles Blundell, Tim Lillicrap, Koray Kavukcuoglu, Daan Wierstra
Matching Networks for One Shot Learning. NIPS (2016)
Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, Timothy P. Lillicrap
Meta-Learning with Memory-Augmented Neural Networks. ICML (2016)
Karol Gregor, Frederic Besse, Danilo Jimenez Rezende, Ivo Danihelka, Daan Wierstra
Towards Conceptual Compression. NIPS (2016)
Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, Daan Wierstra
Continuous control with deep reinforcement learning. ICLR (Poster) (2016)
Danilo Jimenez Rezende, Shakir Mohamed, Ivo Danihelka, Karol Gregor, Daan Wierstra
One-Shot Generalization in Deep Generative Models. CoRR (2016)
Chrisantha Fernando, Dylan Banarse, Malcolm Reynolds, Frederic Besse, David Pfau, Max Jaderberg, Marc Lanctot, Daan Wierstra
Convolution by Evolution: Differentiable Pattern Producing Networks. GECCO (2016)
Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, Timothy P. Lillicrap
One-shot Learning with Memory-Augmented Neural Networks. CoRR (2016)
Chrisantha Fernando, Dylan Banarse, Malcolm Reynolds, Frederic Besse, David Pfau, Max Jaderberg, Marc Lanctot, Daan Wierstra
Convolution by Evolution: Differentiable Pattern Producing Networks. CoRR (2016)
Karol Gregor, Ivo Danihelka, Alex Graves, Daan Wierstra
DRAW: A Recurrent Neural Network For Image Generation. CoRR (2015)
Charles Blundell, Julien Cornebise, Koray Kavukcuoglu, Daan Wierstra
Weight Uncertainty in Neural Network. ICML (2015)
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin A. Riedmiller, Andreas Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, Demis Hassabis
Human-level control through deep reinforcement learning. Nat. 518 (7540) (2015)
Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, Daan Wierstra
DRAW: A Recurrent Neural Network For Image Generation. ICML (2015)
Charles Blundell, Julien Cornebise, Koray Kavukcuoglu, Daan Wierstra
Weight Uncertainty in Neural Networks. CoRR (2015)
Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra
Deep AutoRegressive Networks. ICML (2014)
Daan Wierstra, Tom Schaul, Tobias Glasmachers, Yi Sun, Jan Peters, Jürgen Schmidhuber
Natural evolution strategies. J. Mach. Learn. Res. 15 (1) (2014)
David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra, Martin A. Riedmiller
Deterministic Policy Gradient Algorithms. ICML (2014)
Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra
Stochastic Back-propagation and Variational Inference in Deep Latent Gaussian Models. CoRR (2014)
Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra
Stochastic Backpropagation and Approximate Inference in Deep Generative Models. ICML (2014)
Karol Gregor, Andriy Mnih, Daan Wierstra
Deep AutoRegressive Networks. CoRR (2013)
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, Martin A. Riedmiller
Playing Atari with Deep Reinforcement Learning. CoRR (2013)
Yi Sun, Daan Wierstra, Tom Schaul, Jürgen Schmidhuber
Efficient Natural Evolution Strategies CoRR (2012)
Daan Wierstra, Tom Schaul, Tobias Glasmachers, Yi Sun, Jürgen Schmidhuber
Natural Evolution Strategies CoRR (2011)
Tom Schaul, Yi Sun, Daan Wierstra, Faustino J. Gomez, Jürgen Schmidhuber
Curiosity-driven optimization. IEEE Congress on Evolutionary Computation (2011)
Danilo Jimenez Rezende, Daan Wierstra, Wulfram Gerstner
Variational Learning for Recurrent Spiking Networks. NIPS (2011)
Tom Schaul, Justin Bayer, Daan Wierstra, Yi Sun, Martin Felder, Frank Sehnke, Thomas Rückstieß, Jürgen Schmidhuber
PyBrain. J. Mach. Learn. Res. 11 (2010)
Thomas Rückstieß, Frank Sehnke, Tom Schaul, Daan Wierstra, Yi Sun, Jürgen Schmidhuber
Exploring parameter space in reinforcement learning. Paladyn J. Behav. Robotics 1 (1) (2010)
Tobias Glasmachers, Tom Schaul, Yi Sun, Daan Wierstra, Jürgen Schmidhuber
Exponential natural evolution strategies. GECCO (2010)
Daan Wierstra, Alexander Förster, Jan Peters, Jürgen Schmidhuber
Recurrent policy gradients. Log. J. IGPL 18 (5) (2010)
Yi Sun, Daan Wierstra, Tom Schaul, Jürgen Schmidhuber
Stochastic search using the natural gradient. ICML (2009)
Tom Schaul, Daan Wierstra, Faustino J. Gomez, Jürgen Schmidhuber, Christian Igel, Julian Togelius
Ontogenetic and Phylogenetic Reinforcement Learning. Künstliche Intell. 23 (3) (2009)
Yi Sun, Daan Wierstra, Tom Schaul, Jürgen Schmidhuber
Efficient natural evolution strategies. GECCO (2009)
Niels van Hoorn, Julian Togelius, Daan Wierstra, Jürgen Schmidhuber
Robust player imitation using multiobjective evolution. IEEE Congress on Evolutionary Computation (2009)
Justin Bayer, Daan Wierstra, Julian Togelius, Jürgen Schmidhuber
Evolving Memory Cell Structures for Sequence Learning. ICANN (2) (2009)
Daan Wierstra, Tom Schaul, Jan Peters, Jürgen Schmidhuber
Natural Evolution Strategies. IEEE Congress on Evolutionary Computation (2008)
Daan Wierstra, Tom Schaul, Jan Peters, Jürgen Schmidhuber
Episodic Reinforcement Learning by Logistic Reward-Weighted Regression. ICANN (1) (2008)
Daan Wierstra, Tom Schaul, Jan Peters, Jürgen Schmidhuber
Fitness Expectation Maximization. PPSN (2008)
Hermann Georg Mayer, Faustino J. Gomez, Daan Wierstra, Istvan Nagy, Alois C. Knoll, Jürgen Schmidhuber
A System for Robotic Heart Surgery that Learns to Tie Knots Using Recurrent Neural Networks. Adv. Robotics 22 (13-14) (2008)
Jürgen Schmidhuber, Daan Wierstra, Matteo Gagliolo, Faustino J. Gomez
Training Recurrent Networks by Evolino. Neural Comput. 19 (3) (2007)
Daan Wierstra, Alexander Förster, Jan Peters, Jürgen Schmidhuber
Solving Deep Memory POMDPs with Recurrent Policy Gradients. ICANN (1) (2007)
Daan Wierstra, Jürgen Schmidhuber
Policy Gradient Critics. ECML (2007)
Jürgen Schmidhuber, Matteo Gagliolo, Daan Wierstra, Faustino J. Gomez
Evolino for recurrent support vector machines. ESANN (2006)
Hermann Georg Mayer, Faustino J. Gomez, Daan Wierstra, Istvan Nagy, Alois C. Knoll, Jürgen Schmidhuber
A System for Robotic Heart Surgery that Learns to Tie Knots Using Recurrent Neural Networks. IROS (2006)
Daan Wierstra, Faustino J. Gomez, Jürgen Schmidhuber
Modeling systems with internal state using evolino. GECCO (2005)
Jürgen Schmidhuber, Matteo Gagliolo, Daan Wierstra, Faustino J. Gomez
Evolino for recurrent support vector machines CoRR (2005)
Jürgen Schmidhuber, Daan Wierstra, Faustino J. Gomez
Evolino: Hybrid Neuroevolution/Optimal Linear Search for Sequence Learning. IJCAI (2005)
Daan Wierstra, Marco A. Wiering
Utile distinction hidden Markov models. ICML (2004)