Department of Engineering Computational and Biological Learning Lab

Publications

2009

1. R Turner, MP Deisenroth, and CE Rasmussen
   System Identification in Gaussian Process Dynamical Systems
   Nonparametric Bayes Workshop at NIPS 2009, Whistler, Canada, December 2009.
   
2. MP Deisenroth and CE Rasmussen
   Efficient Reinforcement Learning for Motor Control
   10th International PhD Workshop on Systems and Control, a Young Generation Viewpoint, Hluboka nad Vltavou, Czech Republic, September 2009.
   download
3. MP Deisenroth, MF Huber, and UD Hanebeck
   Analytic Moment-based Gaussian Process Filtering
   in Proceedings of the 26th International Conference on Machine Learning (ICML 2009), pp. 225–232, Omnipress.
   download
4. MP Deisenroth and CE Rasmussen
   Bayesian Inference for Efficient Learning in Control
   in Multidisciplinary Symposium on Reinforcement Learning (MSRL), Montreal, Canada, June 2009.
   download
5. MP Deisenroth, CE Rasmussen, and J Peters
   Gaussian Process Dynamic Programming
   in Neurocomputing, vol. 72, no 7–9, pp. 1508–1524, Elsevier, March 2009.
   download

2008

1. CE Rasmussen and MP Deisenroth
   Probabilistic Inference for Fast Learning in Control
   chapter in Recent Advances in Reinforcement Learning, Lecture Notes on Computer Science, LNAI series, vol. 5323, pp. 229–242, Springer-Verlag, November 2008.
   download
2. MP Deisenroth, J Peters, and CE Rasmussen
   Approximate Dynamic Programming with Gaussian Processes
   in Proceedings of the 2008 American Control Conference (ACC 2008), pp. 4480–4485, June 2008, Seattle, WA, USA.
   download
3. MP Deisenroth, CE Rasmussen, and J Peters
   Model-Based Reinforcement Learning with Continuous States and Actions
   in Proceedings of the European Symposium on Artificial Neural Networks (ESANN 2008), pp. 19–24, April 2008, Bruges, Belgium.
   download

2007

1. MP Deisenroth, F Weissel, T Ohtsuka, and UD Hanebeck
   Online-Computation Approach to Optimal Control of Noise-Affected Nonlinear Systems with Continuous State and Control Spaces
   Proceedings of the 9th European Control Conference 2007 (ECC 2007), pp. 3664–3671, July 2007, Kos, Greece.
   download

2006

1. MP Deisenroth, F Weissel, T Ohtsuka, D Brunn, and UD Hanebeck
   Finite-Horizon Optimal State-Feedback Control of Nonlinear Stochastic Systems Based on a Minimum Principle
   Proceedings of the 6th IEEE International Conference on Multisensor Fusion and Integration (MFI 2006), pp. 371–376, September 2006, Heidelberg, Germany.
   download

Posters

1. MP Deisenroth and CE Rasmussen
   Bayesian Inference for Efficient Learning in Control
   Microsoft Research Summer School, Cambridge, UK, June 2009
   [pdf] [link]
   
2. MP Deisenroth and CE Rasmussen
   Bayesian Inference for Efficient Learning in Control
   Multidisciplinary Symposium on Reinforcement Learning, Montreal, Canada, June 2009
   [pdf] [abstract] [link]
   
3. MP Deisenroth, MF Huber, and UD Hanebeck
   Analytic Moment-based Gaussian Process Filtering
   International Conference on Machine Learning, Montreal, Canada, June 2009
   [pdf] [paper] [discussion] [link]
   
4. MP Deisenroth and CE Rasmussen
   Bayesian Inference for Fast Learning Control
   Cambridge, UK, October 2008
   
5. MP Deisenroth, F Doshi, M Lengyel, CE Rasmussen, and Z Ghahramani
   System that Learn to Make Decisions
   HORIZON Seminar: The Thinking Machine, Cambridge, UK, March 2008
   [pdf]
6. MP Deisenroth, CE Rasmussen, and J Peters
   Dynamic Programming with Gaussian Process Models
   EPSRC Winter School: Mathematics for Data Modelling, Sheffield, UK, January 2008
   [pdf]