Results 51 to 60 of about 871 (187)
Spatial depth for data in metric spaces
Scandinavian Journal of Statistics, EarlyView.Abstract We propose a novel measure of statistical depth, the metric spatial depth, for data residing in an arbitrary metric space. The measure assigns high (low) values for points located near (far away from) the bulk of the data distribution, allowing quantifying their centrality/outlyingness.
Joni Virta
wiley +1 more source
Nonlinear Dimensionality Reduction Based on HSIC Maximization
IEEE Access, 2018 Hilbert-Schmidt independence criterion (HSIC) is typically used to measure the statistical dependence between two sets of data. HSIC first transforms these two sets of data into two reproducing Kernel Hilbert spaces (RKHS), respectively, and then ...
Zhengming Ma +3 more
doaj +1 more source
The Journal of Physiology, EarlyView.Abstract figure legend We present a shape modelling‐based morphological analysis of sex differences in cardiac anatomy. We conduct our analysis on 456 healthy subjects from the UK Biobank (227M/229F) to uncover sex‐based differences in healthy cardiac morphology.
Beatrice Moscoloni +4 more
wiley +1 more source
Operator Reproducing Kernel Hilbert Spaces
, 2015 54 ...
Wang, Rui, Xu, Yuesheng
openaire +2 more sources
Jan Stochel, a stellar mathematician [PDF]
Opuscula MathematicaThe occasion for this survey article was the 70th birthday of Jan Stochel, professor at Jagiellonian University, former head of the Chair of Functional Analysis and a prominent member of the Kraków school of operator theory.
Sameer Chavan +4 more
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The Journal of Physiology, EarlyView.Abstact figure legend A panoramic 3D optical mapping system was developed, enabling imaging of action potential waves across the entire strongly deforming ventricular surface of beating isolated hearts. The system comprises 12 high‐speed cameras and a soccerball‐shaped imaging chamber with 48 light‐emitting diodes (LEDs).
Shrey Chowdhary +5 more
wiley +1 more source
Reproducing Kernel Hilbert Spaces and fractal interpolation
Journal of Computational and Applied Mathematics, 2011 The main result of this work is to link two fields: fractal interpolation and reproducing kernel Hilbert space. The corresponding spaces of the simple fractal interpolation functions are also reproducing kernel Hilbert spaces, as specific cases. The authors provide the elements for calculating the respective kernel functions for reproducing kernel ...
Bouboulis, P., Mavroforakis, M.
openaire +2 more sources
Magnetic Resonance in Medicine, Volume 95, Issue 4, Page 2131-2152, April 2026.ABSTRACT Purpose In multi‐shot EPI, shot‐dependent phase fluctuations can introduce ghost artifacts, undermining advantages for enhancing resolution or reducing distortion, particularly in diffusion scans. Here, a novel self‐navigation strategy based on shift‐invariant kernel extraction is proposed, enabling robust estimation of phase inconsistencies ...
Rui Tian +3 more
wiley +1 more source
Testing Hypotheses of Covariate Effects on Topics of Discourse
Statistical Analysis and Data Mining: An ASA Data Science Journal, Volume 19, Issue 2, April 2026.ABSTRACT We introduce an approach to topic modeling with document‐level covariates that remains tractable in the face of large text corpora. This is achieved by de‐emphasizing the role of parameter estimation in an underlying probabilistic model, assuming instead that the data come from a fixed but unknown distribution whose statistical functionals are
Gabriel Phelan, David A. Campbell
wiley +1 more source
Functional models for Nevanlinna families [PDF]
Opuscula Mathematica, 2008 The class of Nevanlinna families consists of \(\mathbb{R}\)-symmetric holomorphic multivalued functions on \(\mathbb{C} \setminus \mathbb{R}\) with maximal dissipative (maximal accumulative) values on \(\mathbb{C}_{+}\) (\(\mathbb{C}_{-}\), respectively)
Jussi Behrndt, Seppo Hassi, Henk de Snoo
doaj