Markus Svensén - researchr alias

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Viewing Publication 1 - 13 from 13

2020

Potential, challenges and future directions for deep learning in prognostics and health management applicationsOlga Fink, Qin Wang, Markus Svensén, Pierre Dersin, Wan-Jui Lee, Melanie Ducoffe. eaai, 92:103678, 2020. [doi]

2005

Robust Bayesian mixture modellingMarkus Svensén, Christopher M. Bishop. ijon, 64:235-252, 2005. [doi]

2004

Robust Bayesian Mixture ModellingChristopher M. Bishop, Markus Svensén. esann 2004: 69-74 [doi]

Distinguishing text from graphics in on-line handwritten inkChristopher M. Bishop, Markus Svensén, Goeffrey E. Hinton. icfhr 2004: 142-147 [doi]

2003

Bayesian Hierarchical Mixtures of ExpertsChristopher M. Bishop, Markus Svensén. uai 2003: 57-64

2002

ICA of fMRI Group Study DataMarkus Svensén, Frithjof Kruggel, Habib Benali. neuroimage, 16(3):551-563, 2002. [doi]

2000

Probabilistic Modelling of Single Trial fMRI DataMarkus Svensén, Frithjof Kruggel, D. Yves von Cramon. tmi, 19(1):25-35, 2000.

1999

Markov Random Field Modelling of fMRI Data Using a Mean Field EM-algorithmMarkus Svensén, Frithjof Kruggel, D. Yves von Cramon. emmcvpr 1999: 317-330

1998

Developments of the generative topographic mappingChristopher M. Bishop, Markus Svensén, Christopher K. I. Williams. ijon, 21(1-3):203-224, 1998. [doi]

GTM: The Generative Topographic MappingChristopher M. Bishop, Markus Svensén, Christopher K. I. Williams. neco, 10(1):215-234, 1998.

1996

GTM: A Principled Alternative to the Self-Organizing MapChristopher M. Bishop, Markus Svensén, Christopher K. I. Williams. nips 1997: 354-360 [doi]

GTM: A Principled Alternative to the Self-Organizing MapChristopher M. Bishop, Markus Svensén, Christopher K. I. Williams. icann 1996: 165-170

1995

EM Optimization of Latent-Variables Density ModelsChristopher M. Bishop, Markus Svensén, Christopher K. I. Williams. nips 1996: 465-471 [doi]

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