Publications of H Nickisch

Loktyushin, A.; Nickisch, H.; Pohmann, R.; Schölkopf, B.: Blind multirigid retrospective motion correction of MR images. Magnetic Resonance in Medicine 73 (4), pp. 1457 - 1468 (2015)

Loktyuschin, A.; Nickisch, H.; Pohmann, R.; Schölkopf, B.: Blind Retrospective Motion Correction of MR Images. Magnetic Resonance in Medicine 70 (6), pp. 1608 - 1618 (2013)

Nickisch, H.: glm-ie: Generalised Linear Models Inference Estimation Toolbox. Journal of Machine Learning Research 13, pp. 1699 - 1703 (2012)

Seeger, M.; Nickisch, H.: Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models. SIAM Journal on Imaging Sciences 4 (1), pp. 166 - 199 (2011)

Rasmussen, C.; Nickisch, H.: Gaussian Processes for Machine Learning (GPML) Toolbox. The Journal of Machine Learning Research 11, pp. 3011 - 3015 (2010)

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), pp. 116 - 126 (2010)

Nickisch, H.; Rasmussen, C.: Approximations for Binary Gaussian Process Classification. The Journal of Machine Learning Research 9, pp. 2035 - 2078 (2008)

Duvenaud, D.; Nickisch, H.; Rasmussen, C.: Additive Gaussian Processes. In: Advances in Neural Information Processing Systems 24, pp. 226 - 234 (Eds. 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)

Seeger, M.; Nickisch, H.: Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference. In: JMLR Workshop and Conference Proceedings, Vol. 15, pp. 652 - 660 (Eds. Gordon, G.; Dunson, D.; Dudik, M.). 14th International Conference on Artificial Intelligence and Statistics (AISTATS 2011), Fort Lauderdale, FL, USA, April 11, 2011 - April 13, 2011. MIT Press, Cambridge, MA, USA (2011)

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, pp. 274 - 281 (Eds. Chellapa, R.; Anandan, P.; Rajagopalan, A.; Narayanan, P.; Torr, P.). Seventh Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2010), Chennai, India, December 12, 2010 - December 15, 2010. ACM Press, Nw York, NY, USA (2010)

Nickisch, H.; Rasmussen, C.: Gaussian Mixture Modeling with Gaussian Process Latent Variable Models. In: DAGM 2010: Pattern Recognition, pp. 271 - 282 (Eds. Goesele, M.; Roth, S.; Kuijper, A.; Schiele, B.; Schindler, K.). 32nd Annual Symposium of the German Association for Pattern Recognition (DAGM 2010), Darmstadt, Germany, September 22, 2010 - September 24, 2010. Springer, Berlin, Germany (2010)

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, pp. 951 - 958. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), Miami Beach, FL, USA, June 20, 2009 - June 25, 2009. IEEE Service Center, Piscataway, NJ, USA (2009)

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, pp. 761 - 768 (Eds. Danyluk, A.; Bottou, L.; Littman, M.). 26th International Conference on Machine Learning, Montreal, Canada, June 14, 2009 - June 18, 2009. ACM Press, New York, NY, USA (2009)

Seeger, M.; Nickisch, H.; Pohmann, R.; Schölkopf, B.: Bayesian Experimental Design of Magnetic Resonance Imaging Sequences. In: Advances in neural information processing systems 21, pp. 1441 - 1448 (Eds. Koller, D.; Schuurmans, D.; Bengio, Y.; Bottou, L.). Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008), Vancouver, BC, Canada, December 08, 2008 - December 10, 2008. Curran, Red Hook, NY, USA (2009)

Seeger, M.; Nickisch, H.: Compressed Sensing and Bayesian Experimental Design. In: ICML '08: Proceedings of the 25th international conference on Machine, pp. 912 - 919 (Eds. Cohen, W.; McCallum, A.; Roweis, S.). 25th International Conference on Machine Learning (ICML 2008), Helsinki, Finland, July 05, 2008 - July 09, 2008. ACM Press, New York, NY, USA (2008)

Loktyushin, A.; Nickisch, H.; Pohmann, R.; Schölkopf, B.: Multi-rigid motion correction of MR images. 30th Annual Scientific Meeting ESMRMB 2013, Toulouse, France (2013)

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)

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)

Loktyushin, A.; Nickisch, H.; Pohmann, R.: Retrospective blind motion correction of MR images. 28th Annual Scientific Meeting ESMRMB 2011, Leipzig, Germany (2011)

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)