Publications with PyBrain

If you have used PyBrain for your published (or unpublished) work, please let us know at and we'll include you in this list. You can cite PyBrain in your paper with the following bibtex reference:
@article{pybrain2010jmlr,
	Author = {Schaul, Tom and Bayer, Justin and Wierstra, Daan and Sun, Yi and 
	          Felder, Martin and Sehnke, Frank and R{\"u}ckstie{\ss}, Thomas and Schmidhuber, J{\"u}rgen},
	Journal = {Journal of Machine Learning Research},
	Pages = {743--746},
	Title = {{PyBrain}},
	Volume = {11},
	Year = {2010}}

2011

Thomas Rückstieß, Christian Osendorfer, Patrick van der Smagt (2011). Sequential Feature Selection for Classification. Proceedings of the Australasian Conference on Artificial Intelligence, AI 2011. download

2010

Tom Schaul, Justin Bayer, Daan Wierstra, Sun Yi, Martin Felder, Frank Sehnke, Thomas Rückstieß, Jürgen Schmidhuber (2010). PyBrain. To appear in: Journal of Machine Learning Research. download

2009

Justin Bayer, Daan Wierstra, Julian Togelius and Jürgen Schmidhuber (2009). Evolving Cell Structures for Sequence Learning. Proceedings of the International Conference on Artificial Neural Networks (ICANN, Cyprus). download

Sun Yi, Daan Wierstra, Tom Schaul and Jürgen Schmidhuber (2009). Stochastic Search using the Natural Gradient. Proceedings of the International Conference on Machine Learning (ICML, Montreal). download

Sun Yi, Daan Wierstra, Tom Schaul and Jürgen Schmidhuber (2009). Efficient Natural Evolution Strategies. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO, Montreal). download

Tom Schaul and Jürgen Schmidhuber (2009). Scalable Neural Networks for Board Games. To appear in: Proceedings of the International Conference on Artificial Neural Networks (ICANN, Cyprus). download

2008

Tom Schaul and Jürgen Schmidhuber (2008). A Scalable Neural Network Architecture for Board Games. Proceedings of the IEEE Symposium on Computational Intelligence and Games (CIG-2008, Perth, Australia). download

Daan Wierstra, Tom Schaul, Jan Peters and Jürgen Schmidhuber (2008). Episodic Reinforcement Learning by Logistic Reward-Weighted Regression. Proceedings of the International Conference on Artificial Neural Networks (ICANN-2008, Prague). download

Frank Sehnke, Christian Osendorfer, Thomas Rückstieß, Alex Graves, Jan Peters, and Jürgen Schmidhuber (2008). Policy gradients with parameter-based exploration for control. In Proceedings of the International Conference on Artificial Neural Networks (ICANN 2008, Prague). download

Daan Wierstra, Tom Schaul, Jan Peters and Jürgen Schmidhuber (2008). Fitness Expectation Maximization. Proceedings of Parallel Problem Solving from Nature (PPSN-2008, Dortmund). download

Julian Togelius, Tom Schaul, Jürgen Schmidhuber and Faustino Gomez (2008). Countering Poisonous Inputs with Memetic Neuroevolution. Proceedings of Parallel Problem Solving from Nature(PPSN-2008, Dortmund). download

Thomas Rückstieß, Martin Felder, and Jürgen Schmidhuber (2008). State-Dependent Exploration for policy gradient methods. In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-2008, Antwerp). download

Daan Wierstra, Tom Schaul, Jan Peters and Jürgen Schmidhuber (2008). Natural Evolution Strategies. Proceedings of IEEE Congress on Evolutionary Computation (CEC-2008, Hongkong).

Thomas Rückstieß, Martin Felder, Frank Sehnke, Alex Graves, Jürgen Schmidhuber (2008). Robot Learning with State-Dependent Exploration. In Proceedings of the International Workshop on Cognition for Technical Systems, Munich, Germany, October 2008. download

Frank Sehnke, Thomas Rückstieß, Jürgen Schmidhuber (2008). Parametric Policy Gradients for Robotics. In Proceedings of the International Workshop on Cognition for Technical Systems, Munich, Germany, October 2008.

2007

Daan Wierstra, Alexander Foerster, Jan Peters and Jürgen Schmidhuber (2007). Solving Deep Memory POMDPs with Recurrent Policy Gradients. In Proceedings of the International Conference on Neural Networks (ICANN-07, Porto).