Hannes Nickisch

Cited by

	All	Since 2018
Citations	8696	5627
h-index	30	24
i10-index	41	34

1300

650

325

975

20092010201120122013201420152016201720182019202020212022202345 98 166 241 288 363 454 595 702 794 970 1042 1213 1157 448

Public access

View all

9 articles

0 articles

available

not available

Based on funding mandates

Co-authors

Michael GrassPhilips Research, Hambug, GermanyVerified email at philips.com
Andrew Gordon WilsonNew York UniversityVerified email at cims.nyu.edu
Carl Edward RasmussenProfessor of Machine Learning, University of CambridgeVerified email at cam.ac.uk
Matthias SeegerPrincipal Applied Scientist, Amazon, BerlinVerified email at amazon.de
Christoph H. LampertInstitute of Science and Technology Austria (ISTA)Verified email at ist.ac.at
Stefan HarmelingProfessor at Technische Universität DortmundVerified email at tu-dortmund.de
Ivo Matteo BaltruschatMedical Imaging Scientist, BayerVerified email at bayer.com
Tobias KnoppProfessor for Biomedical Imaging, UKE and TUHH, HamburgVerified email at knoppweb.de
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH ZürichVerified email at tuebingen.mpg.de
Sven PrevrhalPhilips Research HamburgVerified email at philips.com
Daniel B. NeillNew York UniversityVerified email at nyu.edu
Michael MorlockProfessor for Biomechanics TUHHVerified email at tuhh.de
Moti FreimanBiomedical Engineering, Technion - Israel Institute of TechnologyVerified email at technion.ac.il
Gerhard AdamRadiologe, UKE, HamburgVerified email at uke.de
Seth Flaxmanassociate professor at OxfordVerified email at cs.ox.ac.uk
David DuvenaudAssociate Professor, University of TorontoVerified email at cs.toronto.edu
Christoph RhemannResearch Scientist, GoogleVerified email at google.com
Carsten RotherProfessor Uni Heidelberg / GermanyVerified email at iwr.uni-heidelberg.de
Alex SmolaBoson AIVerified email at smola.org
Jürgen WeeseResearch Fellow, Philips ResearchVerified email at philips.com

Hannes Nickisch

Philips Research

Verified email at philips.com - Homepage

Medical Image Processing Probabilistic Pattern Recognition Machine Learning Biophysical Simulations Patient-Specific Models


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
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	2629	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	1636	2013
Gaussian processes for machine learning (GPML) toolbox CE Rasmussen, H Nickisch The Journal of Machine Learning Research 11, 3011-3015, 2010	1085	2010
Kernel interpolation for scalable structured Gaussian processes (KISS-GP) A Wilson, H Nickisch International conference on machine learning, 1775-1784, 2015	494	2015
Approximations for binary Gaussian process classification H Nickisch, CE Rasmussen Journal of Machine Learning Research 9 (Oct), 2035-2078, 2008	440	2008
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	349	2019
Additive gaussian processes DK Duvenaud, H Nickisch, C Rasmussen Advances in neural information processing systems 24, 2011	346	2011
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	175	2010
Compressed sensing and Bayesian experimental design MW Seeger, H Nickisch Proceedings of the 25th international conference on Machine learning, 912-919, 2008	133	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	110	2015
Thoughts on massively scalable Gaussian processes AG Wilson, C Dann, H Nickisch arXiv preprint arXiv:1511.01870, 2015	99	2015
Blind retrospective motion correction of MR images A Loktyushin, H Nickisch, R Pohmann, B Schölkopf Magnetic resonance in medicine 70 (6), 1608-1618, 2013	95	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	85	2017
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	85	2011
Method of determining the blood flow through coronary arteries M Grass, H Schmitt, H Nickisch US Patent 9,867,584, 2018	56	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	49	2015
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	47	2018
Learning patient-specific lumped models for interactive coronary blood flow simulations H Nickisch, Y Lamash, S Prevrhal, M Freiman, M Vembar, L Goshen, ... Medical Image Computing and Computer-Assisted Intervention--MICCAI 2015 …, 2015	35	2015
Attribute-based classification for zero-shot learning of object categories CH Lampert, H Nickisch, S Harmeling IEEE Transactions on Pattern Analysis & Machine Intelligence, 1-1, 2013	34	2013
Motion artifact recognition and quantification in coronary CT angiography using convolutional neural networks T Lossau, H Nickisch, T Wissel, R Bippus, H Schmitt, M Morlock, M Grass Medical image analysis 52, 68-79, 2019	33	2019

The system can't perform the operation now. Try again later.

Articles 1–20

Citations per year

Duplicate citations

Merged citations

Add co-authorsCo-authors

Follow

Cited by

Co-authors