Publikationen von H Nickisch

Zeitschriftenartikel (7)

1.
Zeitschriftenartikel
Loktyushin, A.; Nickisch, H.; Pohmann, R.; Schölkopf, B.: Blind multirigid retrospective motion correction of MR images. Magnetic Resonance in Medicine 73 (4), S. 1457 - 1468 (2015)
2.
Zeitschriftenartikel
Loktyuschin, A.; Nickisch, H.; Pohmann, R.; Schölkopf, B.: Blind Retrospective Motion Correction of MR Images. Magnetic Resonance in Medicine 70 (6), S. 1608 - 1618 (2013)
3.
Zeitschriftenartikel
Nickisch, H.: glm-ie: Generalised Linear Models Inference Estimation Toolbox. Journal of Machine Learning Research 13, S. 1699 - 1703 (2012)
4.
Zeitschriftenartikel
Seeger, M.; Nickisch, H.: Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models. SIAM Journal on Imaging Sciences 4 (1), S. 166 - 199 (2011)
5.
Zeitschriftenartikel
Rasmussen, C.; Nickisch, H.: Gaussian Processes for Machine Learning (GPML) Toolbox. The Journal of Machine Learning Research 11, S. 3011 - 3015 (2010)
6.
Zeitschriftenartikel
Seeger, M.; Nickisch, H.; Pohmann, R.; Schölkopf, B.: Optimization of k-Space Trajectories for Compressed Sensing by Bayesian Experimental Design. Magnetic Resonance in Medicine 63 (1), S. 116 - 126 (2010)
7.
Zeitschriftenartikel
Nickisch, H.; Rasmussen, C.: Approximations for Binary Gaussian Process Classification. The Journal of Machine Learning Research 9, S. 2035 - 2078 (2008)

Konferenzbeitrag (8)

8.
Konferenzbeitrag
Duvenaud, D.; Nickisch, H.; Rasmussen, C.: Additive Gaussian Processes. In: Advances in Neural Information Processing Systems 24, S. 226 - 234 (Hg. Shawe-Taylor, J.; Zemel, R.; Bartlett, P.; Pereira, F.; Weinberger, K.). Twenty-Fifth Annual Conference on Neural Information Processing Systems (NIPS 2011), Granada, Spain. Curran, Red Hook, NY, USA (2012)
9.
Konferenzbeitrag
Seeger, M.; Nickisch, H.: Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference. In: JMLR Workshop and Conference Proceedings, Bd. 15, S. 652 - 660 (Hg. Gordon, G.; Dunson, D.; Dudik, M.). 14th International Conference on Artificial Intelligence and Statistics (AISTATS 2011), Fort Lauderdale, FL, USA, 11. April 2011 - 13. April 2011. MIT Press, Cambridge, MA, USA (2011)
10.
Konferenzbeitrag
Nickisch, H.; Rother, C.; Kohli, P.; Rhemann, C.: Learning an interactive segmentation system. In: ICVGIP '10: Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing, S. 274 - 281 (Hg. Chellapa, R.; Anandan, P.; Rajagopalan, A.; Narayanan, P.; Torr, P.). Seventh Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2010), Chennai, India, 12. Dezember 2010 - 15. Dezember 2010. ACM Press, Nw York, NY, USA (2010)
11.
Konferenzbeitrag
Nickisch, H.; Rasmussen, C.: Gaussian Mixture Modeling with Gaussian Process Latent Variable Models. In: DAGM 2010: Pattern Recognition, S. 271 - 282 (Hg. Goesele, M.; Roth, S.; Kuijper, A.; Schiele, B.; Schindler, K.). 32nd Annual Symposium of the German Association for Pattern Recognition (DAGM 2010), Darmstadt, Germany, 22. September 2010 - 24. September 2010. Springer, Berlin, Germany (2010)
12.
Konferenzbeitrag
Lampert, C.; Nickisch, H.; Harmeling, S.: Learning To Detect Unseen Object Classes by Between-Class Attribute Transfer. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, S. 951 - 958. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), Miami Beach, FL, USA, 20. Juni 2009 - 25. Juni 2009. IEEE Service Center, Piscataway, NJ, USA (2009)
13.
Konferenzbeitrag
Nickisch, H.; Seeger, M.: Convex variational Bayesian inference for large scale generalized linear models. In: ICML '09: Proceedings of the 26th Annual International Conference on Machine Learning, S. 761 - 768 (Hg. Danyluk, A.; Bottou, L.; Littman, M.). 26th International Conference on Machine Learning, Montreal, Canada, 14. Juni 2009 - 18. Juni 2009. ACM Press, New York, NY, USA (2009)
14.
Konferenzbeitrag
Seeger, M.; Nickisch, H.; Pohmann, R.; Schölkopf, B.: Bayesian Experimental Design of Magnetic Resonance Imaging Sequences. In: Advances in neural information processing systems 21, S. 1441 - 1448 (Hg. Koller, D.; Schuurmans, D.; Bengio, Y.; Bottou, L.). Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008), Vancouver, BC, Canada, 08. Dezember 2008 - 10. Dezember 2008. Curran, Red Hook, NY, USA (2009)
15.
Konferenzbeitrag
Seeger, M.; Nickisch, H.: Compressed Sensing and Bayesian Experimental Design. In: ICML '08: Proceedings of the 25th international conference on Machine, S. 912 - 919 (Hg. Cohen, W.; McCallum, A.; Roweis, S.). 25th International Conference on Machine Learning (ICML 2008), Helsinki, Finland, 05. Juli 2008 - 09. Juli 2008. ACM Press, New York, NY, USA (2008)

Vortrag (2)

16.
Vortrag
Loktyushin, A.; Nickisch, H.; Pohmann, R.; Schölkopf, B.: Multi-rigid motion correction of MR images. 30th Annual Scientific Meeting ESMRMB 2013, Toulouse, France (2013)
17.
Vortrag
Seeger, M.; Nickisch, H.; Pohmann, R.; Schölkopf, B.: Bayesian Experimental Design of MRI Sequences. Workshop on Machine Learning: Approaches to Representational Learning and Recognition in Vision, Frankfurt a.M., Germany (2008)

Poster (4)

18.
Poster
Loktyushin, A.; Nickisch, H.; Pohmann, R.; Schölkopf, B.: Blind Retrospective Motion Correction of MR Images. 20th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM 2012), Melbourne, Australia (2012)
19.
Poster
Loktyushin, A.; Nickisch, H.; Pohmann, R.: Retrospective blind motion correction of MR images. 28th Annual Scientific Meeting ESMRMB 2011, Leipzig, Germany (2011)
20.
Poster
Lippert, C.; Stegle, O.; Nickisch, H.; Borgwardt, K.; Weigel, D.: Experimental design for genome-wide association studies. 18th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB 2010), Boston, MA, USA (2010)
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