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Dr. Carl Edward Rasmussen

Address:	Spemannstr. 38 72076 Tübingen
Fax:	+49-7071-601-552
E-Mail:	carl

Carl Edward Rasmussen

Position: Research Scientist Unit: Alumni Schölkopf

Publications

Books (1):
•	Rasmussen CE and Williams CKI : Gaussian Processes for Machine Learning, 248, MIT Press, Cambridge, MA, USA, (January-2006).
Proceedings (1):
•	Rasmussen CE , Bülthoff HH , Giese MA and Schölkopf B : Pattern Recognition: 26th DAGM Symposium, 26th Pattern Recognition Symposium, 581, Springer, Berlin, Germany, (August-2004). 978-3-540-22945-2
Articles (13):
•	Rasmussen CE and Nickisch H (November-2010) Gaussian Processes for Machine Learning (GPML) Toolbox Journal of Machine Learning Research 11 3011-3015.
•	Görür D and Rasmussen CE (July-2010) Dirichlet Process Gaussian Mixture Models: Choice of the Base Distribution Journal of Computer Science and Technology 25(4) 653-664.
•	Lázaro-Gredilla M , Quiñonero-Candela J , Rasmussen CE and Figueiras-Vidal AR (June-2010) Sparse Spectrum Gaussian Process Regression Journal of Machine Learning Research 11 1865-1881.
•	Rasmussen CE , de la Cruz BJ , Ghahramani Z and Wild DL (October-2009) Modeling and Visualizing Uncertainty in Gene Expression Clusters using Dirichlet Process Mixtures IEEE/ACM Transactions on Computational Biology and Bioinformatics 6(4) 615-628.
•	Deisenroth MP , Rasmussen CE and Peters J (March-2009) Gaussian Process Dynamic Programming Neurocomputing 72(7-9) 1508-1524.
•	Nickisch H and Rasmussen CE (October-2008) Approximations for Binary Gaussian Process Classification Journal of Machine Learning Research 9 2035-2078.
•	Sonnenburg S , Braun ML , Ong CS , Bengio S , Bottou L , Holmes G , LeCun Y , Müller K-R , Pereira F , Rasmussen CE , Rätsch G , Schölkopf B , Smola A , Vincent P , Weston J and Williamson RC (October-2007) The Need for Open Source Software in Machine Learning Journal of Machine Learning Research 8 2443-2466.
•	Pfingsten T , Herrmann D and Rasmussen CE (February-2006) Model-based Design Analysis and Yield Optimization IEEE Transactions on Semiconductor Manufacturing 19(4) 475-486.
•	Quinonero Candela J and Rasmussen CE (December-2005) A Unifying View of Sparse Approximate Gaussian Process Regression Journal of Machine Learning Research 6 1935-1959.
•	Kuss M and Rasmussen C (October-2005) Assessing Approximate Inference for Binary Gaussian Process Classification Journal of Machine Learning Research 6 1679.
•	Andersen IK , Szymkowiak A , Rasmussen CE , Hanson LG , Marstrand JR , Larsson HBW and Hansen LK (2002) Perfusion Quantification using Gaussian Process Deconvolution Magnetic Resonance in Medicine (48) 351-361.
•	Hansen LK and Rasmussen CE (1994) Pruning from Adaptive Regularization Neural Computation 6(6) 1222-1231.
•	Rasmussen CE and Willshaw DJ (1993) Presynaptic and Postsynaptic Competition in models for the Development of Neuromuscular Connections Biological Cybernetics 68 409-419.
Conference papers (34):
•	Duvenaud D , Nickisch H and Rasmussen CA (January-2012) Additive Gaussian Processes In: Advances in Neural Information Processing Systems 24, Twenty-Fifth Annual Conference on Neural Information Processing Systems (NIPS 2011), 226-234.
•	Nickisch H and Rasmussen CE (September-2010) Gaussian Mixture Modeling with Gaussian Process Latent Variable Models In: Pattern Recognition, 32nd Annual Symposium of the German Association for Pattern Recognition (DAGM 2010), Springer, Berlin, Germany, 271-282.
•	Rasmussen CE and Deisenroth MP (November-2008) Probabilistic Inference for Fast Learning in Control In: EWRL 2008, 8th European Workshop on Reinforcement Learning, Springer, Berlin, Germany, 229-242.
•	Deisenroth MP , Peters J and Rasmussen CE (June-2008) Approximate Dynamic Programming with Gaussian Processes In: ACC 2008, 2008 American Control Conference, IEEE Service Center, Piscataway, NJ, USA, 4480-4485.
•	Deisenroth MP , Rasmussen CE and Peters J (April-2008) Model-Based Reinforcement Learning with Continuous States and Actions In: ESANN 2008, European Symposium on Artificial Neural Networks, d-side, Evere, Belgium, 19-24.
•	Görür D , Jäkel F and Rasmussen CE (June-2006) A Choice Model with Infinitely Many Latent Features In: ICML 2006, 23rd International Conference on Machine Learning, ACM Press, New York, NY, USA, 361-368.
•	Kuss M and Rasmussen CE (May-2006) Assessing Approximations for Gaussian Process Classification In: Advances in neural information processing systems 18, Nineteenth Annual Conference on Neural Information Processing Systems (NIPS 2005), MIT Press, Cambridge, MA, USA, 699-706.
•	Quinonero Candela J , Rasmussen CE , Sinz F , Bousquet O and Schölkopf B (April-2006) Evaluating Predictive Uncertainty Challenge In: Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment, First PASCAL Machine Learning Challenges Workshop (MLCW 2005), Springer, Berlin, Germany, 1-27.
•	Quinonero Candela J and Rasmussen CE (2005) Analysis of Some Methods for Reduced Rank Gaussian Process Regression In: Switching and Learning in Feedback Systems, European Summer School on Multi-Agent Control 2003, Springer, Berlin, Germany, 98-127.
•	Rasmussen CE and Candela JQ (2005) Healing the Relevance Vector Machine through Augmentation ICML 2005, 689.
•	Sinz F , Candela JQ , BakIr G , Rasmussen CE and Franz M (September-2004) Learning Depth From Stereo In: 26th DAGM Symposium, 26th DAGM Symposium, Springer, Berlin, Germany, 245-252.
•	Görür D , Rasmussen CE , Tolias AS , Sinz F and Logothetis NK (September-2004) Modelling Spikes with Mixtures of Factor Analysers In: Pattern Recognition, 26th DAGM Symposium, Springer, Berlin, Germany, 391-398.
•	Rasmussen CE and Kuss M (June-2004) Gaussian Processes in Reinforcement Learning In: Advances in Neural Information Processing Systems 16, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), MIT Press, Cambridge, MA, USA, 751-759.
•	Eichhorn J , Tolias AS , Zien A , Kuss M , Rasmussen CE , Weston J , Logothetis NK and Schölkopf B (June-2004) Prediction on Spike Data Using Kernel Algorithms In: Advances in Neural Information Processing Systems 16, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), MIT Press, Cambridge, MA, USA, 1367-1374.
•	Snelson E , Rasmussen CE and Ghahramani Z (June-2004) Warped Gaussian Processes In: Advances in Neural Information Processing Systems 16, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), MIT Press, Cambridge, MA, USA, 337-344.
•	Dubey A , Hwang S , Rangel C , Rasmussen CE , Ghahramani Z and Wild DL (2004) Clustering Protein Sequence and Structure Space with Infinite Gaussian Mixture Models Pacific Symposium on Biocomputing 2004, World Scientific Publishing, Singapore, 399-410.
•	Kocijan J , Murray-Smith R , Rasmussen CE and Girard A (2004) Gasussian process model based predictive control Proceedings of the ACC 2004, 2214-2219.
•	Franz MO , Kwon Y , Rasmussen CE and Schölkopf B (2004) Semi-supervised kernel regression using whitened function classes Pattern Recognition, Proceedings of the 26th DAGM Symposium, LNCS 3175, 18-26.
•	Rasmussen CE and Ghahramani Z (October-2003) Bayesian Monte Carlo In: Advances in Neural Information Processing Systems 15, Sixteenth Annual Conference on Neural Information Processing Systems (NIPS 2002), MIT Press, Cambridge, MA, USA, 489-496.
•	Solak E , Murray-Smith R , Leithead WE , Leith D and Rasmussen CE (October-2003) Derivative observations in Gaussian Process models of dynamic systems In: Advances in Neural Information Processing Systems 15, Sixteenth Annual Conference on Neural Information Processing Systems (NIPS 2002), MIT Press, Cambridge, MA, USA, 1033-1040.
•	Girard A , Rasmussen CE , Quiñonero-Candela J and Murray-Smith R (October-2003) Multiple-step ahead prediction for non linear dynamic systems: A Gaussian Process treatment with propagation of the uncertainty In: Advances in Neural Information Processing Systems 15, Sixteenth Annual Conference on Neural Information Processing Systems (NIPS 2002), MIT Press, Cambridge, MA, USA, 529-536.
•	Murray-Smith R , Sbarbaro D , Rasmussen CE and Girard A (August-2003) Adaptive, Cautious, Predictive control with Gaussian Process Priors Proceedings of the 13th IFAC Symposium on System Identification, 1195-1200.
•	Kocijan J , Banko B , Likar B , Girard A , Murray-Smith R and Rasmussen CE (April-2003) A case based comparison of identification with neural network and Gaussian process models. Proceedings of the International Conference on Intelligent Control Systems and Signal Processing ICONS 2003, 1, 137-142.
•	Rasmussen CE (2003) Gaussian Processes to Speed up Hybrid Monte Carlo for Expensive Bayesian Integrals Bayesian Statistics 7, 651-659.
•	Kocijan J , Murray-Smith R , Rasmussen CE and Likar B (2003) Predictive control with Gaussian process models Proceedings of IEEE Region 8 Eurocon 2003: Computer as a Tool, 352-356.
•	Quiñonero-Candela J , Girard A , Larsen J and Rasmussen CE (2003) Propagation of Uncertainty in Bayesian Kernel Models - Application to Multiple-Step Ahead Forecasting Proceedings of 2003 IEEE International Workshop on Neural Networks for Signal Processing, 0-0.
•	Quiñonero-Candela J , Girard A , Larsen J and Rasmussen CE (2003) Propagation of Uncertainty in Bayesian Kernel Models - Application to Multiple-Step Ahead Forecasting IEEE International Conference on Acoustics, Speech and Signal Processing, 2, 701-704.
•	Beal MJ , Ghahramani Z and Rasmussen CE (September-2002) The Infinite Hidden Markov Model In: Advances in Neural Information Processing Systems 14, Fifteenth Annual Neural Information Processing Systems Conference (NIPS 2001), MIT Press, Cambridge, MA, USA, 577-584.
•	Rasmussen CE and Ghahramani Z (2002) Infinite Mixtures of Gaussian Process Experts .
•	Rasmussen CE and Ghahramani Z (April-2001) Occam's Razor In: Advances in Neural Information Processing Systems 13, Fourteenth Annual Neural Information Processing Systems Conference (NIPS 2000), MIT Press, Cambridge, MA, USA, 294-300.
•	Rasmussen CE (June-2000) The Infinite Gaussian Mixture Model In: Advances in Neural Information Processing Systems 12, Thirteenth Annual Neural Information Processing Systems Conference (NIPS 1999), MIT Press, Cambridge, MA, USA, 554-560.
•	PADFR , Rasmussen CE and Hansen LK (2000) Bayesian modelling of fMRI time series , 754-760.
•	Rasmussen CE (June-1996) A practical Monte Carlo implementation of Bayesian learning In: Advances in Neural Information Processing Systems 8, Ninth Annual Conference on Neural Information Processing Systems (NIPS 1995), MIT Press, Cambridge, MA, USA, 598-604.
•	Williams CKI and Rasmussen CE (June-1996) Gaussian Processes for Regression In: Advances in neural information processing systems 8, Ninth Annual Conference on Neural Information Processing Systems (NIPS 1995), MIT Press, Cambridge, MA, USA, 514-520.
Contributions to books (2):
•	Quiñonero-Candela J , Rasmussen CE and Williams CKI : Approximation Methods for Gaussian Process Regression, 203-223. In: Large-Scale Kernel Machines, (Ed) L. Bottou, MIT Press, Cambridge, MA, USA, (September-2007).