Author of the publication

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Unsupervised Learning of Multiple Aspects of Moving Objects from Video.

M. Titsias, and C. Williams. Panhellenic Conference on Informatics, volume 3746 of Lecture Notes in Computer Science, page 746-756. Springer, (2005)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

K. Stahl

K. Gaiser

K. Lindow

Grzegorz K. Karch

Dipl.-Ing. Thomas Kuestner

Scan time reduction in DWI of the pancreas using simultaneous multislice technique with different acceleration factors: how fast can we go?J. Taron, P. Martirosian, T. Küstner, M. Notohamiprodjo, J. Weiß, A. Othman, K. Nikolaou, and C. Schraml. Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM), Honolulu, Hawaii, USA, (April 2017)

Scan time reduction in DWI of the pancreas using simultaneous multislice technique with different acceleration factors: how fast can we go?J. Taron, P. Martirosian, T. Küstner, M. Notohamiprodjo, J. Weiß, A. Othman, K. Nikolaou, and C. Schraml. Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM), Honolulu, Hawaii, USA, (April 2017)The use of a generalized reconstruction by inversion of coupled systems (GRICS) approach for generic respiratory motion correction in PET/MR imagingH. Fayad, F. Odille, H. Schmidt, C. Würslin, T. Küstner, J. Felblinger, and D. Visvikis. Physics in medicine and biology, 60 (6): 2529-46 (March 2015)In-vivo MR-derived non-rigid motion correction of simultaneously acquired PETT. Küstner, C. Würslin, S. Gatidis, P. Martirosian, N. Schwenzer, B. Yang, and H. Schmidt. Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM), Toronto, Canada, (June 2015)

Other publications of authors with the same name

Inference for determinantal point processes without spectral knowledge.R. Bardenet, and M. Titsias. NIPS, page 3393-3401. (2015)Spike and Slab Variational Inference for Multi-Task and Multiple Kernel Learning.M. Titsias, and M. Lázaro-Gredilla. NIPS, page 2339-2347. (2011)Variational Inference for Latent Variables and Uncertain Inputs in Gaussian Processes.A. Damianou, M. Titsias, and N. Lawrence. J. Mach. Learn. Res., (2016)Augmented Ensemble MCMC sampling in Factorial Hidden Markov Models.K. Märtens, M. Titsias, and C. Yau. AISTATS, volume 89 of Proceedings of Machine Learning Research, page 2359-2367. PMLR, (2019)Variational Learning of Inducing Variables in Sparse Gaussian Processes.M. Titsias. AISTATS, volume 5 of JMLR Proceedings, page 567-574. JMLR.org, (2009)A Probabilistic RBF Network for Classification.M. Titsias, and A. Likas. IJCNN (4), page 238-243. IEEE Computer Society, (2000)0-7695-0619-4.Unsupervised Learning of Multiple Aspects of Moving Objects from Video.M. Titsias, and C. Williams. Panhellenic Conference on Informatics, volume 3746 of Lecture Notes in Computer Science, page 746-756. Springer, (2005)Unbiased Implicit Variational Inference.M. Titsias, and F. Ruiz. CoRR, (2018)Statistical Inference in Hidden Markov Models using $k$-segment Constraints.M. Titsias, C. Yau, and C. Holmes. CoRR, (2013)Fast Unsupervised Greedy Learning of Multiple Objects and Parts from Video.M. Titsias, and C. Williams. CVPR Workshops, page 179. IEEE Computer Society, (2004)