23 results
(BibTeX)

**Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference **
In *JMLR Workshop and Conference Proceedings Volume 15: AISTATS 2011*, pages: 652-660, (Editors: Gordon, G. , D. Dunson, M. Dudík ), MIT Press, Cambridge, MA, USA, 14th International Conference on Artificial Intelligence and Statistics, April 2011 (inproceedings)

**Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models**
*SIAM Journal on Imaging Sciences*, 4(1):166-199, March 2011 (article)

**Model based reconstruction for GRE EPI**
*Magnetic Resonance Materials in Physics, Biology and Medicine*, 24(Supplement 1):493-494, 28th Annual Scientific Meeting ESMRMB, October 2011 (poster)

**Multiple Kernel Learning: A Unifying Probabilistic Viewpoint**
Max Planck Institute for Biological Cybernetics, March 2011 (techreport)

**Large Scale Variational Inference and Experimental Design for Sparse Generalized Linear Models**
Max Planck Institute for Biological Cybernetics, August 2010 (techreport)

**Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference**
Max Planck Institute for Biological Cybernetics, December 2010 (techreport)

**Optimization of k-Space Trajectories for Compressed Sensing by Bayesian Experimental Design**
*Magnetic Resonance in Medicine*, 63(1):116-126, January 2010 (article)

**Real-Time Local GP Model Learning**
In *From Motor Learning to Interaction Learning in Robots*, pages: 193-207, Studies in Computational Intelligence ; 264, (Editors: Sigaud, O. , J. Peters), Springer, Berlin, Germany, January 2010 (inbook)

**Local Gaussian Process Regression for Real Time Online Model Learning and Control**
In *Advances in neural information processing systems 21 : 22nd Annual Conference on Neural Information Processing Systems 2008*, *Advances in neural information processing systems 21*, pages: 1193-1200, (Editors: Koller, D. , D. Schuurmans, Y. Bengio, L. Bottou), Curran, Red Hook, NY, USA, Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS), June 2009 (inproceedings)

**Optimization of k-Space Trajectories by Bayesian Experimental Design**
17(2627), 17th Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM), April 2009 (poster)

**Model Learning with Local Gaussian Process Regression**
*Advanced Robotics*, 23(15):2015-2034, November 2009 (article)

**Cross-validation Optimization for Large Scale Structured Classification Kernel Methods**
*Journal of Machine Learning Research*, 9, pages: 1147-1178, June 2008 (article)

**Bayesian Inference for Spiking Neuron Models with a Sparsity Prior**
In *Advances in Neural Information Processing Systems 20: 21st Annual Conference on Neural Information Processing Systems 2007*, *Advances in neural information processing systems 20*, pages: 529-536, (Editors: Platt, J. C., D. Koller, Y. Singer, S. Roweis), Curran, Red Hook, NY, USA, Twenty-First Annual Conference on Neural Information Processing Systems (NIPS), September 2008 (inproceedings)

**Learning Inverse Dynamics: A Comparison**
In *Advances in Computational Intelligence and Learning: Proceedings of the European Symposium on Artificial Neural Networks (ESANN 2008)*, *Advances in Computational Intelligence and Learning: Proceedings of the European Symposium on Artificial Neural Networks*, pages: 13-18, (Editors: M Verleysen), d-side, Evere, Belgium, 16th European Symposium on Artificial Neural Networks (ESANN), April 2008 (inproceedings)

**Computed Torque Control with Nonparametric Regression Models**
In *Proceedings of the 2008 American Control Conference (ACC 2008)*, *ACC 2008*, pages: 212-217, IEEE Service Center, Piscataway, NJ, USA, 2008 American Control Conference, June 2008 (inproceedings)

**Cross-Validation Optimization for Large Scale Hierarchical
Classification Kernel Methods**
In *Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference*, *Advances in Neural Information Processing Systems 19*, pages: 1233-1240, (Editors: Schölkopf, B. , J. Platt, T. Hofmann), MIT Press, Cambridge, MA, USA, Twentieth Annual Conference on Neural Information Processing Systems (NIPS), September 2007 (inproceedings)

**Experimental design for efficient identification of gene regulatory networks using sparse Bayesian models**
*BMC Systems Biology*, 1(51):1-15, November 2007 (article)

**Bayesian Inference and Optimal Design in the Sparse Linear Model**
In *Proceedings of the 11th International Conference on Artificial Intelligence and Statistics (AISTATS 2007)*, *JMLR Workshop and Conference Proceedings Volume 2: AISTATS 2007*, pages: 444-451, (Editors: Meila, M. , X. Shen), JMLR, Cambridge, MA, USA, 11th International Conference on Artificial Intelligence and Statistics, March 2007 (inproceedings)

**Bayesian Inference for Sparse Generalized Linear Models**
In *Machine Learning: ECML 2007*, *ECML 2007*, pages: 298-309, Lecture Notes in Computer Science ; 4701, (Editors: Kok, J. N., J. Koronacki, R. Lopez de Mantaras, S. Matwin, D. Mladenic, A. Skowron), Springer, Berlin, Germany, 18th European Conference on Machine Learning, September 2007 (inproceedings)

**Bayesian Neural System identification: error bars, receptive fields and neural couplings**
*31st G{\"o}ttingen Neurobiology Conference*, 31, pages: 360, March 2007 (poster)