Hannes Nickisch
Zitiert von
Zitiert von
Learning to detect unseen object classes by between-class attribute transfer
CH Lampert, H Nickisch, S Harmeling
2009 IEEE conference on computer vision and pattern recognition, 951-958, 2009
Attribute-based classification for zero-shot visual object categorization
CH Lampert, H Nickisch, S Harmeling
IEEE transactions on pattern analysis and machine intelligence 36 (3), 453-465, 2013
Gaussian processes for machine learning (GPML) toolbox
CE Rasmussen, H Nickisch
The Journal of Machine Learning Research 11, 3011-3015, 2010
Approximations for binary Gaussian process classification
H Nickisch, CE Rasmussen
Journal of Machine Learning Research 9 (Oct), 2035-2078, 2008
Kernel interpolation for scalable structured Gaussian processes (KISS-GP)
A Wilson, H Nickisch
International conference on machine learning, 1775-1784, 2015
Additive gaussian processes
DK Duvenaud, H Nickisch, C Rasmussen
Advances in neural information processing systems 24, 2011
Comparison of deep learning approaches for multi-label chest X-ray classification
IM Baltruschat, H Nickisch, M Grass, T Knopp, A Saalbach
Scientific reports 9 (1), 1-10, 2019
Optimization of k‐space trajectories for compressed sensing by Bayesian experimental design
M Seeger, H Nickisch, R Pohmann, B Schölkopf
Magnetic Resonance in Medicine: An Official Journal of the International …, 2010
Compressed sensing and Bayesian experimental design
MW Seeger, H Nickisch
Proceedings of the 25th international conference on Machine learning, 912-919, 2008
Fast Kronecker inference in Gaussian processes with non-Gaussian likelihoods
S Flaxman, A Wilson, D Neill, H Nickisch, A Smola
International Conference on Machine Learning, 607-616, 2015
Thoughts on massively scalable Gaussian processes
AG Wilson, C Dann, H Nickisch
arXiv preprint arXiv:1511.01870, 2015
Large scale Bayesian inference and experimental design for sparse linear models
MW Seeger, H Nickisch
SIAM Journal on Imaging Sciences 4 (1), 166-199, 2011
Blind retrospective motion correction of MR images
A Loktyushin, H Nickisch, R Pohmann, B Schölkopf
Magnetic resonance in medicine 70 (6), 1608-1618, 2013
Scalable log determinants for Gaussian process kernel learning
K Dong, D Eriksson, H Nickisch, D Bindel, AG Wilson
Advances in Neural Information Processing Systems 30, 2017
Method of determining the blood flow through coronary arteries
M Grass, H Schmitt, H Nickisch
US Patent 9,867,584, 2018
Blind multirigid retrospective motion correction of MR images
A Loktyushin, H Nickisch, R Pohmann, B Schölkopf
Magnetic resonance in medicine 73 (4), 1457-1468, 2015
Fast convergent algorithms for expectation propagation approximate Bayesian inference
M Seeger, H Nickisch
Proceedings of the Fourteenth International Conference on Artificial …, 2011
Learning an interactive segmentation system
H Nickisch, C Rother, P Kohli, C Rhemann
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics …, 2010
Convex variational Bayesian inference for large scale generalized linear models
H Nickisch, MW Seeger
Proceedings of the 26th Annual International Conference on Machine Learning …, 2009
Automatic classification of auroral images from the Oslo Auroral THEMIS (OATH) data set using machine learning
LBN Clausen, H Nickisch
Journal of Geophysical Research: Space Physics 123 (7), 5640-5647, 2018
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