Steffen Udluft

Thomas Martinetz, Steffen Udluft, Daniel Schneegaß, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning

Finale Doshi-Velez, Steffen Udluft, José Miguel Hernández-Lobato, 2017, ICML.

Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks pdf

Finale Doshi-Velez, Steffen Udluft, José Miguel Hernández-Lobato, 2016, ICLR.

Improving Optimality of Neural Rewards Regression for Data-Efficient Batch Near-Optimal Policy Identification

Thomas Martinetz, Steffen Udluft, Daniel Schneegaß, 2007, ICANN.

Learning Long Term Dependencies with Recurrent Neural Networks

Steffen Udluft, Hans-Georg Zimmermann, Anton Maximilian Schäfer, 2006, ICANN.

Dateneffizientes Reinforcement-Learning

Steffen Udluft, Volkmar Sterzing, 2009, Künstliche Intell..

Ensemble Usage for More Reliable Policy Identification in Reinforcement Learning

Steffen Udluft, Alexander Hans, S. Udluft, 2011, ESANN.

Explicit Kernel Rewards Regression for data-efficient near-optimal policy identification

Thomas Martinetz, Steffen Udluft, Daniel Schneegaß, 2007, ESANN.

Overcoming Model Bias for Robust Offline Deep Reinforcement Learning pdf

Steffen Udluft, Thomas Runkler, Phillip Swazinna, 2020, Eng. Appl. Artif. Intell..

Uncertainty Propagation for Efficient Exploration in Reinforcement Learning

Steffen Udluft, Alexander Hans, 2010, ECAI.

Kernel Rewards Regression: An Information Efficient Batch Policy Iteration Approach

Thomas Martinetz, Steffen Udluft, Daniel Schneegaß, 2006, Artificial Intelligence and Applications.

Thomas A. Runkler, Alexander Hentschel, Steffen Udluft, 2015, ESANN.

Decomposition of Uncertainty for Active Learning and Reliable Reinforcement Learning in Stochastic Systems pdf

Finale Doshi-Velez, Steffen Udluft, José Miguel Hernández-Lobato, 2017, ArXiv.

Ensembles for Continuous Actions in Reinforcement Learning

Steffen Udluft, Siegmund Düll, S. Udluft, 2013, ESANN.

Ensembles of Neural Networks for Robust Reinforcement Learning

Steffen Udluft, Alexander Hans, S. Udluft, 2010, 2010 Ninth International Conference on Machine Learning and Applications.

Solving Partially Observable Reinforcement Learning Problems with Recurrent Neural Networks

Steffen Udluft, Volkmar Sterzing, Siegmund Düll, 2012, Neural Networks: Tricks of the Trade.

Measuring Data Quality for Dataset Selection in Offline Reinforcement Learning

Steffen Udluft, Thomas Runkler, Phillip Swazinna, 2021, 2021 IEEE Symposium Series on Computational Intelligence (SSCI).

Behavior Constraining in Weight Space for Offline Reinforcement Learning pdf

Steffen Udluft, Daniel Hein, Thomas Runkler, 2021, ESANN.

Comparing Model-free and Model-based Algorithms for Offline Reinforcement Learning pdf

Steffen Udluft, Daniel Hein, Thomas Runkler, 2022, IFAC-PapersOnLine.

Sensitivity analysis for predictive uncertainty in Bayesian neural networks

Thomas A. Runkler, Steffen Udluft, José Miguel Hernández-Lobato, 2018 .