Carl Edward Rasmussen

	2009
30		Marc Peter Deisenroth, Carl Edward Rasmussen, Jan Peters: Gaussian process dynamic programming. Neurocomputing 72(7-9): 1508-1524 (2009)
	2008
29		Marc Peter Deisenroth, Carl Edward Rasmussen, Jan Peters: Model-Based Reinforcement Learning with Continuous States and Actions. ESANN 2008: 19-24
28		Carl Edward Rasmussen, Marc Peter Deisenroth: Probabilistic Inference for Fast Learning in Control. EWRL 2008: 229-242
	2006
27		Dilan Görür, Frank Jäkel, Carl Edward Rasmussen: A choice model with infinitely many latent features. ICML 2006: 361-368
	2005
26		Carl Edward Rasmussen, Joaquin Quiñonero Candela: Healing the relevance vector machine through augmentation. ICML 2005: 689-696
25		Joaquin Quiñonero Candela, Carl Edward Rasmussen, Fabian H. Sinz, Olivier Bousquet, Bernhard Schölkopf: Evaluating Predictive Uncertainty Challenge. MLCW 2005: 1-27
24		Malte Kuss, Carl Edward Rasmussen: Assessing Approximations for Gaussian Process Classification. NIPS 2005
23		Malte Kuss, Carl Edward Rasmussen: Assessing Approximate Inference for Binary Gaussian Process Classification. Journal of Machine Learning Research 6: 1679-1704 (2005)
22		Joaquin Quiñonero Candela, Carl Edward Rasmussen: A Unifying View of Sparse Approximate Gaussian Process Regression. Journal of Machine Learning Research 6: 1939-1959 (2005)
	2004
21		Carl Edward Rasmussen, Heinrich H. Bülthoff, Bernhard Schölkopf, Martin A. Giese: Pattern Recognition, 26th DAGM Symposium, August 30 - September 1, 2004, Tübingen, Germany, Proceedings Springer 2004
20		Matthias O. Franz, Younghee Kwon, Carl Edward Rasmussen, Bernhard Schölkopf: Semi-supervised Kernel Regression Using Whitened Function Classes. DAGM-Symposium 2004: 18-26
19		Fabian H. Sinz, Joaquin Quiñonero Candela, Gökhan H. Bakir, Carl Edward Rasmussen, Matthias O. Franz: Learning Depth from Stereo. DAGM-Symposium 2004: 245-252
18		Dilan Görür, Carl Edward Rasmussen, Andreas S. Tolias, Fabian H. Sinz, Nikos Logothetis: Modelling Spikes with Mixtures of Factor Analysers. DAGM-Symposium 2004: 391-398
17		Ananya Dubey, Seungwoo Hwang, Claudia Rangel, Carl Edward Rasmussen, Zoubin Ghahramani, David L. Wild: Clustering Protein Sequence and Structure Space with Infinite Gaussian Mixture Models. Pacific Symposium on Biocomputing 2004: 399-410
	2003
16		Carl Edward Rasmussen: Gaussian Processes in Machine Learning. Advanced Lectures on Machine Learning 2003: 63-71
15		Joaquin Quiñonero Candela, Carl Edward Rasmussen: Analysis of Some Methods for Reduced Rank Gaussian Process Regression. European Summer School on Multi-AgentControl 2003: 98-127
14		Carl Edward Rasmussen, Malte Kuss: Gaussian Processes in Reinforcement Learning. NIPS 2003
13		Jan Eichhorn, Andreas S. Tolias, Alexander Zien, Malte Kuss, Carl Edward Rasmussen, Jason Weston, Nikos Logothetis, Bernhard Schölkopf: Prediction on Spike Data Using Kernel Algorithms. NIPS 2003
12		Edward Snelson, Carl Edward Rasmussen, Zoubin Ghahramani: Warped Gaussian Processes. NIPS 2003
	2002
11		E. Solak, Roderick Murray-Smith, William E. Leithead, Douglas J. Leith, Carl Edward Rasmussen: Derivative Observations in Gaussian Process Models of Dynamic Systems. NIPS 2002: 1033-1040
10		Carl Edward Rasmussen, Zoubin Ghahramani: Bayesian Monte Carlo. NIPS 2002: 489-496
9		Agathe Girard, Carl Edward Rasmussen, Joaquin Quiñonero Candela, Roderick Murray-Smith: Gaussian Process Priors with Uncertain Inputs - Application to Multiple-Step Ahead Time Series Forecasting. NIPS 2002: 529-536
	2001
8		Matthew J. Beal, Zoubin Ghahramani, Carl Edward Rasmussen: The Infinite Hidden Markov Model. NIPS 2001: 577-584
7		Carl Edward Rasmussen, Zoubin Ghahramani: Infinite Mixtures of Gaussian Process Experts. NIPS 2001: 881-888
	2000
6		Carl Edward Rasmussen, Zoubin Ghahramani: Occam's Razor. NIPS 2000: 294-300
	1999
5		Carl Edward Rasmussen: The Infinite Gaussian Mixture Model. NIPS 1999: 554-560
4		Pedro A. d. F. R. Højen-Sørensen, Lars Kai Hansen, Carl Edward Rasmussen: Bayesian Modelling of fMRI lime Series. NIPS 1999: 754-760
	1995
3		Christopher K. I. Williams, Carl Edward Rasmussen: Gaussian Processes for Regression. NIPS 1995: 514-520
2		Carl Edward Rasmussen: A Practical Monte Carlo Implementation of Bayesian Learning. NIPS 1995: 598-604
	1994
1		Lars Kai Hansen, Carl Edward Rasmussen: Pruning from Adaptive Regularization. Neural Computation 6(6): 1223-1232 (1994)

Coauthor Index

1	Gökhan H. Bakir	[19]
2	Matthew J. Beal	[8]
3	Olivier Bousquet	[25]
4	Heinrich H. Bülthoff	[21]
5	Joaquin Quiñonero Candela	[9] [15] [19] [22] [25] [26]
6	Marc Peter Deisenroth	[28] [29] [30]
7	Ananya Dubey	[17]
8	Jan Eichhorn	[13]
9	Matthias O. Franz	[19] [20]
10	Zoubin Ghahramani	[6] [7] [8] [10] [12] [17]
11	Martin A. Giese	[21]
12	Agathe Girard	[9]
13	Dilan Görür	[18] [27]
14	Lars Kai Hansen	[1] [4]
15	Pedro A. d. F. R. Højen-Sørensen	[4]
16	Seungwoo Hwang	[17]
17	Frank Jäkel	[27]
18	Malte Kuss	[13] [14] [23] [24]
19	Younghee Kwon	[20]
20	Douglas J. Leith	[11]
21	William E. Leithead	[11]
22	Nikos Logothetis	[13] [18]
23	Roderick Murray-Smith	[9] [11]
24	Jan Peters	[29] [30]
25	Claudia Rangel	[17]
26	Bernhard Schölkopf	[13] [20] [21] [25]
27	Fabian H. Sinz	[18] [19] [25]
28	Edward Snelson	[12]
29	E. Solak	[11]
30	Andreas S. Tolias	[13] [18]
31	Jason Weston	[13]
32	David L. Wild	[17]
33	Christopher K. I. Williams	[3]
34	Alexander Zien	[13]

Colors in the list of coauthors