Results 61 to 70 of about 73,738 (309)

Geodesic Mappings onto Generalized m-Ricci-Symmetric Spaces

Mathematics, 2022
In this paper, we study geodesic mappings of spaces with affine connections onto generalized 2-, 3-, and m-Ricci-symmetric spaces. In either case, the main equations for the mappings are obtained as a closed system of linear differential equations of the Cauchy type in the covariant derivatives.
Volodymyr Berezovski, Yevhen Cherevko, Irena Hinterleitner, Patrik Peška   +3 more
openaire   +3 more sources

Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review

Advanced Intelligent Discovery, EarlyView.
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang, Jiayi Tan, Qizhen Song, Tian Du, Jens Hauch, Christoph J. Brabec   +5 more
wiley   +1 more source

Exponentially Harmonic Maps into Spheres

Axioms, 2018
We study smooth exponentially harmonic maps from a compact, connected, orientable Riemannian manifold M into a sphere S m ⊂ R m + 1 .
Sorin Dragomir, Francesco Esposito
doaj   +1 more source

Machine learning holographic mapping by neural network renormalization group

Physical Review Research, 2020
Exact holographic mapping (EHM) provides an explicit duality map between a conformal field theory (CFT) configuration and a massive field propagating on an emergent classical geometry.
Hong-Ye Hu, Shuo-Hui Li, Lei Wang, Yi-Zhuang You   +3 more
doaj   +1 more source

Riemannian Geometry for the Classification of Brain States with Intracortical Brain Recordings

Advanced Intelligent Systems, EarlyView.
Geometric machine learning is applied to decode brain states from invasive intracortical neural recordings, extending Riemannian methods to the invasive regime where data is scarcer and less stationary. A Minimum Distance to Mean classifier on covariance manifolds uses geodesic distances to outperform convolutional neural networks while reducing ...
Arnau Marin‐Llobet, Sergio Sánchez‐Manso, Arnau Manasanch, Lluc Tresserras, Xinhe Zhang, Yining Hua, Hao Zhao, Melody Torao‐Angosto, Maria V Sanchez‐Vives, Leonardo Dalla Porta   +9 more
wiley   +1 more source

Weak mixing suspension flows over shifts of finite type are universal [PDF]

, 2012
Let S be an ergodic measure-preserving automorphism on a non-atomic probability space, and let T be the time-one map of a topologically weak mixing suspension flow over an irreducible subshift of finite type under a Holder ceiling function.
Quas, Anthony, Soo, Terry
core   +1 more source

Optisense: Computational Optimization for Strain Sensor Placement in Wearable Motion Tracking Systems

Advanced Intelligent Systems, EarlyView.
A computational framework for optimizing strain sensor placement in wearable motion tracking systems is presented. By combining dense strain mapping with a genetic algorithm, the method discovers counterintuitive yet highly effective configurations that reduce joint angle error by 32%.
Minu Kim, Juhyung Ahn, Jieun Seo, Steve Park, Joo Yong Sim   +4 more
wiley   +1 more source

Holographic thermal entropy from geodesic bit threads

Journal of High Energy Physics
The holographic bit threads are an insightful tool to investigate the holographic entanglement entropy and other quantities related to the bipartite entanglement in AdS/CFT.
Stefania Caggioli, Francesco Gentile, Domenico Seminara, Erik Tonni   +3 more
doaj   +1 more source

An Improved Boosting Learning Saliency Method for Built-Up Areas Extraction in Sentinel-2 Images

Remote Sensing, 2018
Built-up areas extraction from satellite images is an important aspect of urban planning and land use; however, this remains a challenging task when using optical satellite images. Existing methods may be limited because of the complex background.
Zhenhui Sun, Qingyan Meng, Weifeng Zhai
doaj   +1 more source

Soliton Dynamics in Computational Anatomy

, 2004
Computational anatomy (CA) has introduced the idea of anatomical structures being transformed by geodesic deformations on groups of diffeomorphisms. Among these geometric structures, landmarks and image outlines in CA are shown to be singular solutions ...
Alain Trouvé, Arnold, Arnold, Ashburner, Bajcsy, Ballmaier, Ballmaier, Bookstein, Camassa, Camion, Cannon, Chen, Csernansky, Darryl D. Holm, Dupuis, Foias, Fringer, Gee, Glaunes, Glaunès, Gogtay, Green, Grenander, Grenander, Grenander, Hallinan, Holm, Holm, Holm, J. Tilak Ratnanather, Jain, Joshi, Laurent Younes, Liu, Miller, Miller, Miller, Montagnat, Mumford, Mumford, Mumford, Mumford, Narr, Narr, Narr, Narr, Posener, Sowell, Sowell, Su, Tepest, Thompson, Thompson, Toga, Toga, Trouvé, Vaillant, Wang, Zeidler, Zeineh   +59 more
core   +2 more sources