Results 1 to 10 of about 1,647 (169)

Local Riemannian geometry of model manifolds and its implications for practical parameter identifiability. [PDF]

open access: yesPLoS ONE, 2019
When non-linear models are fitted to experimental data, parameter estimates can be poorly constrained albeit being identifiable in principle. This means that along certain paths in parameter space, the log-likelihood does not exceed a given statistical ...
Daniel Lill, Jens Timmer, Daniel Kaschek
doaj   +6 more sources

PADA: perturbation-aware differential Riemannian attention for robust motor imagery decoding [PDF]

open access: yesFrontiers in Neuroscience
IntroductionRiemannian geometry models have significantly improved the robustness and performance of EEG-based motor imagery decoding and are better suited to small sample sizes; however, their ability to extract nonlinear and spatiotemporal variability ...
Jianxiu Li   +16 more
doaj   +2 more sources

Information-Geometric Detection via Local SPD Structure Fields in the Time–Frequency Domain [PDF]

open access: yesEntropy
Non-stationary signal detection is challenging when discriminative information is not reflected in global energy, mean spectra, or a single covariance statistic, but is instead embedded in the organization of local time–frequency structures.
Yaohao Yue, Benjie Wei, Yang Yang
doaj   +2 more sources

Tensor invariants of generalized Kenmotsu manifolds [PDF]

open access: yesE3S Web of Conferences, 2021
In this paper, we study the properties of generalized Kenmotsu manifolds, consider the second-order differential geometric invariants of the Riemannian curvature tensor of generalized Kenmotsu manifolds (by the symmetry properties of the Riemannian ...
Shihab Ali Abdul Al Majeed   +1 more
doaj   +1 more source

An Approach to Fisher-Rao Metric for Infinite Dimensional Non-Parametric Information Geometry [PDF]

open access: yesEntropy
Non-parametric information geometry has long faced an “intractability barrier”: in the infinite-dimensional setting, the Fisher–Rao metric is a weak Riemannian metric functional that lacks a bounded inverse, rendering classical optimization and ...
Bing Cheng, Howell Tong
doaj   +2 more sources

Semi-Invariant Riemannian Submersions with Semi-Symmetric Non-Metric Connection

open access: yesJournal of New Theory, 2021
In this paper, we investigate semi-invariant Riemannian submersion from a Kaehler manifold with semi-symmetric non-metric connection to a Riemannian manifold. We study the geometry of foliations with semi-symmetric non-metric connection.
Ramazan Sarı
doaj   +1 more source

On the Geometry of the Riemannian Curvature Tensor of Nearly Trans-Sasakian Manifolds

open access: yesAxioms, 2023
This paper presents the results of fundamental research into the geometry of the Riemannian curvature tensor of nearly trans-Sasakian manifolds. The components of the Riemannian curvature tensor on the space of the associated G-structure are counted, and
Aligadzhi R. Rustanov
doaj   +1 more source

Geodesics in the TPS Space

open access: yesMathematics, 2022
In shape analysis, the interpolation of shapes’ trajectories is often performed by means of geodesics in an appropriate Riemannian Shape Space. Over the past several decades, different metrics and shape spaces have been proposed, including Kendall shape ...
Valerio Varano   +5 more
doaj   +1 more source

Intrinsic fractional Taylor formula

open access: yesBruno Pini Mathematical Analysis Seminar, 2022
We consider a class of non-local ultraparabolic Kolmogorov operators and a suitable fractional Holder spaces that take into account the intrinsic sub-riemannian geometry induced by the operators.
Maria Manfredini
doaj   +1 more source

Quantum State Assignment Flows

open access: yesEntropy, 2023
This paper introduces assignment flows for density matrices as state spaces for representation and analysis of data associated with vertices of an underlying weighted graph.
Jonathan Schwarz   +5 more
doaj   +1 more source

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