Contact

Dr. Carl Edward Rasmussen

Adresse: Spemannstr. 38
72076 Tübingen
Fax: 07071-601-552

 

Bild von Rasmussen, Carl Edward, Dr.

Carl Edward Rasmussen

Position: Wissenschaftler  Abteilung: 

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Bücher (1):

Rasmussen CE und Williams CKI: Gaussian Processes for Machine Learning, 248, MIT Press, Cambridge, MA, USA, (Januar-2006). ISBN: 0-262-18253-X, Series: Adaptive Computation and Machine Learning

Tagungsbände (1):

Rasmussen CE, Bülthoff HH, Giese MA und Schölkopf B: Pattern Recognition: 26th DAGM Symposium, 26th Annual Symposium of the German Association for Pattern Recognition (DAGM 2004), 581, Springer, Berlin, Germany, (September-2004).
978-3-540-22945-2, Series: Lecture Notes in Computer Science ; 3175

Artikel (13):

Rasmussen CE und Nickisch H (November-2010) Gaussian Processes for Machine Learning (GPML) Toolbox Journal of Machine Learning Research 11 3011-3015.
Görür D und Rasmussen CE (Juli-2010) Dirichlet Process Gaussian Mixture Models: Choice of the Base Distribution Journal of Computer Science and Technology 25(4) 653-664.
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Lázaro-Gredilla M, Quiñonero-Candela J, Rasmussen CE und Figueiras-Vidal AR (Juni-2010) Sparse Spectrum Gaussian Process Regression Journal of Machine Learning Research 11 1865-1881.
Rasmussen CE, de la Cruz BJ, Ghahramani Z und Wild DL (Oktober-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.
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Deisenroth MP, Rasmussen CE und Peters J (März-2009) Gaussian Process Dynamic Programming Neurocomputing 72(7-9) 1508-1524.
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Nickisch H und Rasmussen CE (Oktober-2008) Approximations for Binary Gaussian Process Classification Journal of Machine Learning Research 9 2035-2078.
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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 und Williamson RC (Oktober-2007) The Need for Open Source Software in Machine Learning Journal of Machine Learning Research 8 2443-2466.
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Pfingsten T, Herrmann D und Rasmussen CE (Februar-2006) Model-based Design Analysis and Yield Optimization IEEE Transactions on Semiconductor Manufacturing 19(4) 475-486.
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Quinonero Candela J und Rasmussen CE (Dezember-2005) A Unifying View of Sparse Approximate Gaussian Process Regression Journal of Machine Learning Research 6 1935-1959.
Kuss M und Rasmussen C (Oktober-2005) Assessing Approximate Inference for Binary Gaussian Process Classification Journal of Machine Learning Research 6 1679.
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Andersen IK, Szymkowiak A, Rasmussen CE, Hanson LG, Marstrand JR, Larsson HBW und Hansen LK (2002) Perfusion Quantification using Gaussian Process Deconvolution Magnetic Resonance in Medicine (48) 351-361.
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Hansen LK und Rasmussen CE (1994) Pruning from Adaptive Regularization Neural Computation 6(6) 1222-1231.
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Rasmussen CE und Willshaw DJ (1993) Presynaptic and Postsynaptic Competition in models for the Development of Neuromuscular Connections Biological Cybernetics 68 409-419.
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Beiträge zu Tagungsbänden (36):

Duvenaud D, Nickisch H und Rasmussen CA (Januar-2012) Additive Gaussian Processes In: Advances in Neural Information Processing Systems 24, , Twenty-Fifth Annual Conference on Neural Information Processing Systems (NIPS 2011), Curran, Red Hook, NY, USA, 226-234.
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Nickisch H und 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, Series: Lecture Notes in Computer Science ; 6376.
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Saatçi Y, Turner R und Rasmussen CE (Juni-2010) Gaussian process change point models, 27th International Conference on Machine Learning (ICML 2010), Curran, Red Hook, NY, USA, 927-934.
Turner R, Deisenroth MP und Rasmussen CE (Mai-2010) State-Space Inference and Learning with Gaussian Processes, Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2010), International Machine Learning Society, Madison, WI, USA, 868-875, Series: JMLR Workshop and Conference Proceedings ; 9.
Rasmussen CE und Deisenroth MP (November-2008) Probabilistic Inference for Fast Learning in Control In: Recent Advances in Reinforcement Learning, , 8th European Workshop on Reinforcement Learning (EWRL 2008), Springer, Berlin, Germany, 229-242, Series: Lecture Notes in Computer Science ; 5323.
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Deisenroth MP, Peters J und Rasmussen CE (Juni-2008) Approximate Dynamic Programming with Gaussian Processes, American Control Conference (ACC 2008), IEEE Service Center, Piscataway, NJ, USA, 4480-4485.
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Deisenroth MP, Rasmussen CE und Peters J (April-2008) Model-Based Reinforcement Learning with Continuous States and Actions In: Advances in computational intelligence and learning, , 16th European Symposium on Artificial Neural Networks (ESANN 2008), D-Side, Evere, Belgium, 19-24.
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Görür D, Jäkel F und Rasmussen CE (Juni-2006) A Choice Model with Infinitely Many Latent Features, 23rd International Conference on Machine Learning (ICML 2006), ACM Press, New York, NY, USA, 361-368.
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Kuss M und Rasmussen CE (Mai-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.
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Quinonero Candela J, Rasmussen CE, Sinz F, Bousquet O und 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, Series: Lecture Notes in Computer Science ; 3944.
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Quinonero Candela J und Rasmussen CE (September-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, Series: Lecture Notes in Computer Science ; 3355.
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Rasmussen CE und Candela JQ (August-2005) Healing the Relevance Vector Machine through Augmentation, 22nd International Conference on Machine Learning (ICML 2005), ACM Press, New York, NY, USA, 689-696.
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Rasmussen CE (September-2004) Gaussian Processes in Machine Learning In: Advanced Lectures on Machine Learning, , ML Summer Schools 2003, Springer, Berlin, Germany, 63-71, Series: Lecture Notes in Computer Science ; 3176.
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Sinz F, Candela JQ, BakIr G, Rasmussen CE und Franz M (September-2004) Learning Depth From Stereo In: Pattern Recognition, , 26th Annual Symposium of the German Association for Pattern Recognition (DAGM 2004), Springer, Berlin, Germany, 245-252, Series: Lecture Notes in Computer Science ; 3175.
Görür D, Rasmussen CE, Tolias AS, Sinz F und Logothetis NK (September-2004) Modelling Spikes with Mixtures of Factor Analysers In: Pattern Recognition, , 26th Annual Symposium of the German Association for Pattern Recognition (DAGM 2004), Springer, Berlin, Germany, 391-398, Series: Lecture Notes in Computer Science ; 3175.
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Franz MO, Kwon Y, Rasmussen CE und Schölkopf B (September-2004) Semi-supervised Kernel Regression Using Whitened Function Classes In: Pattern Recognition, , 26th Annual Symposium of the German Association for Pattern Recognition (DAGM 2004), Springer, Berlin, Germany, 18-26, Series: Lecture Notes in Computer Science ; 3175.
Kocijan J, Murray-Smith R, Rasmussen CE und Girard A (Juli-2004) Gasussian process model based predictive control, American Control Conference (ACC 2004), IEEE Service Center, Piscataway, NJ, USA, 2214-2219.
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Rasmussen CE und Kuss M (Juni-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.
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Eichhorn J, Tolias AS, Zien A, Kuss M, Rasmussen CE, Weston J, Logothetis NK und Schölkopf B (Juni-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.
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Snelson E, Rasmussen CE und Ghahramani Z (Juni-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.
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Dubey A, Hwang S, Rangel C, Rasmussen CE, Ghahramani Z und Wild DL (Januar-2004) Clustering Protein Sequence and Structure Space with Infinite Gaussian Mixture Models, Pacific Symposium on Biocomputing (PSB 2004), World Scientific, Singapore, 399-410.
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Rasmussen CE und Ghahramani Z (Oktober-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.
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Solak E, Murray-Smith R, Leithead WE, Leith D und Rasmussen CE (Oktober-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.
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Girard A, Rasmussen CE, Quiñonero-Candela J und Murray-Smith R (Oktober-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.
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Kocijan J, Murray-Smith R, Rasmussen CE und Likar B (September-2003) Predictive control with Gaussian process models, IEEE Region 8 Eurocon 2003: Computer as a Tool, IEEE, Piscataway, NJ, USA, 352-356.
Murray-Smith R, Sbarbaro D, Rasmussen CE und Girard A (August-2003) Adaptive, Cautious, Predictive control with Gaussian Process Priors, 13th IFAC Symposium on System Identification (SYSID '03), Elsevier, Oxford, UK, 1195-1200.
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Kocijan J, Banko B, Likar B, Girard A, Murray-Smith R und Rasmussen CE (April-2003) A case based comparison of identification with neural network and Gaussian process models, IFAC International Conference on Intelligent Control Systems and Signal Processing (ICONS 2003), Pergamon, Oxford, UK, 137-142.
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Quiñonero-Candela J, Girard A, Larsen J und Rasmussen CE (April-2003) Propagation of Uncertainty in Bayesian Kernel Models: Application to Multiple-Step Ahead Forecasting, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '03), IEEE, Piscataway, NJ, USA, 701-704.
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Rasmussen CE (2003) Gaussian Processes to Speed up Hybrid Monte Carlo for Expensive Bayesian Integrals, Bayesian Statistics 7, Bayesian Statistics 7, 651-659.
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Beal MJ, Ghahramani Z und 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.
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Rasmussen CE und Ghahramani Z (2002) Infinite Mixtures of Gaussian Process Experts.
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Rasmussen CE und 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.
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Rasmussen CE (Juni-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.
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PADFR, Rasmussen CE und Hansen LK (2000) Bayesian modelling of fMRI time series, 754-760.
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Rasmussen CE (Juni-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.
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Last updated: Montag, 22.05.2017