Results 81 to 90 of about 2,282 (200)

Lower Bounds for the Integrated and Minimax Risks in Intrinsic Statistical Estimation: A Geometric Approach

Mathematics
In parametric statistics, it is well established that the canonical measures of estimator performance—such as bias, variance, and mean squared error—are inherently dependent on the parameterization of the model.
José Manuel Corcuera, José María Oller   +1 more
doaj   +1 more source

An extended definition of Anosov representation for relatively hyperbolic groups

Journal of Topology, Volume 19, Issue 2, June 2026.
Abstract We define a new family of discrete representations of relatively hyperbolic groups which unifies many existing definitions and examples of geometrically finite behavior in higher rank. The definition includes the relative Anosov representations defined by Kapovich–Leeb and Zhu, and Zhu–Zimmer, as well as holonomy representations of various ...
Theodore Weisman
wiley   +1 more source

Martingales on manifolds and geometric Ito calculus [PDF]

This work studies properties of stochastic processes taking values in a differential manifold M with a linear connection Γ, or in a Riemannian manifold with a metric connection.
Darling, R. W. R.
core  

Nonlinear Methods in Riemannian and Kählerian Geometry

, 1991
In this book, I present an expanded version of the contents of my lectures at a Seminar of the DMV (Deutsche Mathematiker Vereinigung) in Düsseldorf, June, 1986.
Jost, Jürgen
core   +1 more source

Einstein Gravity, Lagrange-Finsler Geometry, and Nonsymmetric Metrics

Symmetry, Integrability and Geometry: Methods and Applications, 2008
We formulate an approach to the geometry of Riemann-Cartan spaces provided with nonholonomic distributions defined by generic off-diagonal and nonsymmetric metrics inducing effective nonlinear and affine connections.
Sergiu I. Vacaru
doaj   +1 more source

Riemannian geometry for efficient analysis of protein dynamics data

, 2023
An increasingly common viewpoint is that protein dynamics data sets reside in a non-linear subspace of low conformational energy. Ideal data analysis tools for such data sets should therefore account for such non-linear geometry.
Esteve-Yagüe, Carlos, Lellmann, Jan, Diepeveen, Willem, Öktem, Ozan, Schönlieb, Carola-Bibiane   +4 more
core  

Inconsistency of point-particle dynamics on higher-spin backgrounds

Journal of High Energy Physics
We use the light-cone gauge formalism to study interactions of point particles with massless higher-spin fields. By analysing the light-cone consistency conditions at the subleading order in higher-spin fields, we find that no local interactions of point
Vyacheslav Ivanovskiy, Dmitry Ponomarev
doaj   +1 more source

RHG-DETR: Riemannian Hyper-Graph Transformer with Dynamic Receptive Fields for Detecting Special Targets in Degraded UAV Imagery

Remote Sensing
Special target detection in UAV remote sensing imagery is challenged by composite multi-type degradation, which collectively erodes target structure across every stage of a detection pipeline.
Kaipeng Wang, Guanglin He, Wenhao Kong, Yuzhe Fu, Zongze Li   +4 more
doaj   +1 more source

Geometric Optimal Transport for Cross-Modal Medical Manifold Alignment: A Differential Approach to Multimodal Diagnosis

IEEE Access
We present a novel theoretical framework for multimodal medical diagnosis that formulates heterogeneous data integration as a problem of aligning Riemannian manifolds through differential geometric principles.
Yuan Shen
doaj   +1 more source

Shape operator of an $ (n-1) $-dimensional distribution on an $ n $-dimensional manifold and their classification [PDF]

ریاضی و جامعه
This paper aims to study of shape operator of an $ (n-1) $-dimensional distribution on an $ n $-dimensional smooth manifold. In this study firstly we state formulae for the shape operator and its symmetric and anti-symmetric components and in ...
Mehran Aminian, Mehran Namjoo
doaj   +1 more source