Stephan Huckemann
Stephan Huckemann
Professor for Non-Euclidean Statistics, University of Goettingen
Bestätigte E-Mail-Adresse bei math.uni-goettingen.de - Startseite
Titel
Zitiert von
Zitiert von
Jahr
A Smeary Central Limit Theorem for Manifolds with Application to High Dimensional Spheres
B Eltzner, SF Huckemann
https://arxiv.org/abs/1801.06581, 2018
204*2018
Intrinsic shape analysis: Geodesic PCA for Riemannian manifolds modulo isometric Lie group actions
S Huckemann, T Hotz, A Munk
Statistica Sinica, 1-58, 2010
1822010
Intrinsic shape analysis: Geodesic PCA for Riemannian manifolds modulo isometric Lie group actions
S Huckemann, T Hotz, A Munk
Statistica Sinica, 1-58, 2010
1822010
Global models for the orientation field of fingerprints: an approach based on quadratic differentials
S Huckemann, T Hotz, A Munk
IEEE transactions on pattern analysis and machine intelligence 30 (9), 1507-1519, 2008
982008
Principal component analysis for Riemannian manifolds, with an application to triangular shape spaces
S Huckemann, H Ziezold
Advances in Applied Probability 38 (2), 299-319, 2006
932006
Sticky central limit theorems on open books
T Hotz, S Huckemann, H Le, JS Marron, JC Mattingly, E Miller, J Nolen, ...
The Annals of Applied Probability 23 (6), 2238-2258, 2013
592013
Nested sphere statistics of skeletal models
SM Pizer, S Jung, D Goswami, J Vicory, X Zhao, R Chaudhuri, JN Damon, ...
Innovations for Shape Analysis, 93-115, 2013
542013
The filament sensor for near real-time detection of cytoskeletal fiber structures
B Eltzner, C Wollnik, C Gottschlich, S Huckemann, F Rehfeldt
PloS one 10 (5), e0126346, 2015
512015
Inference on 3d procrustes means: Tree bole growth, rank deficient diffusion tensors and perturbation models
S Huckemann
Scandinavian Journal of Statistics 38 (3), 424-446, 2011
472011
Intrinsic MANOVA for Riemannian manifolds with an application to Kendall's space of planar shapes
S Huckemann, T Hotz, A Munk
IEEE Transactions on Pattern Analysis and Machine Intelligence 32 (4), 593-603, 2009
462009
Intrinsic inference on the mean geodesic of planar shapes and tree discrimination by leaf growth
SF Huckemann
The Annals of Statistics 39 (2), 1098-1124, 2011
432011
Filter design and performance evaluation for fingerprint image segmentation
DH Thai, S Huckemann, C Gottschlich
PloS one 11 (5), e0154160, 2016
392016
Intrinsic means on the circle: Uniqueness, locus and asymptotics
T Hotz, S Huckemann
Annals of the Institute of Statistical Mathematics 67 (1), 177-193, 2015
392015
Möbius deconvolution on the hyperbolic plane with application to impedance density estimation
SF Huckemann, PT Kim, JY Koo, A Munk
The Annals of Statistics 38 (4), 2465-2498, 2010
282010
On the meaning of mean shape: manifold stability, locus and the two sample test
SF Huckemann
Annals of the Institute of Statistical Mathematics 64 (6), 1227-1259, 2012
272012
Tree-oriented analysis of brain artery structure
S Skwerer, E Bullitt, S Huckemann, E Miller, I Oguz, M Owen, ...
Journal of mathematical imaging and vision 50 (1-2), 126-143, 2014
262014
Separating the real from the synthetic: minutiae histograms as fingerprints of fingerprints
C Gottschlich, S Huckemann
IET Biometrics 3 (4), 291-301, 2014
262014
Principal component geodesics for planar shape spaces
S Huckemann, T Hotz
Journal of Multivariate Analysis 100 (4), 699-714, 2009
262009
Torus principal component analysis with applications to RNA structure
B Eltzner, S Huckemann, KV Mardia
The Annals of Applied Statistics 12 (2), 1332-1359, 2018
202018
Analysis of rotational deformations from directional data
J Schulz, S Jung, S Huckemann, M Pierrynowski, JS Marron, SM Pizer
Journal of Computational and Graphical Statistics 24 (2), 539-560, 2015
192015
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