| 2008 | ESANN | Safe exploration for reinforcement learning. | Alexander Hans, Daniel Schneega, Anton Maximilian Schfer, Steffen Udluft |
| 2008 | IJCNN | Uncertainty propagation for quality assurance in Reinforcement Learning. | Daniel Schneega, Steffen Udluft, Thomas Martinetz |
| 2007 | ESANN | The Intrinsic Recurrent Support Vector Machine. | Daniel Schneega, Anton Maximilian Schfer, Thomas Martinetz |
| 2007 | ESANN | Neural Rewards Regression for near-optimal policy identification in Markovian and partial observable environments. | Daniel Schneega, Steffen Udluft, Thomas Martinetz |
| 2007 | ESANN | Explicit Kernel Rewards Regression for data-efficient near-optimal policy identification. | Daniel Schneega, Steffen Udluft, Thomas Martinetz |
| 2007 | ICANN | Improving Optimality of Neural Rewards Regression for Data-Efficient Batch Near-Optimal Policy Identification. | Daniel Schneega, Steffen Udluft, Thomas Martinetz |
| 2007 | IJCNN | A Neural Reinforcement Learning Approach to Gas Turbine Control. | Anton Maximilian Schfer, Daniel Schneega, Volkmar Sterzing, Steffen Udluft |
| 2006 | ESANN | OnlineDoubleMaxMinOver: a simple approximate time and information efficient online Support Vector Classification method. | Daniel Schneega, Thomas Martinetz, Michael Clausohm |
| 2006 | ICANN | MaxMinOver Regression: A Simple Incremental Approach for Support Vector Function Approximation. | Daniel Schneega, Kai Labusch, Thomas Martinetz |
| 2005 | ICANN | SoftDoubleMinOver: A Simple Procedure for Maximum Margin Classification. | Thomas Martinetz, Kai Labusch, Daniel Schneega |