Results 31 to 40 of about 427,912 (276)
Learning neural operators on Riemannian manifolds
National Science OpenLearning mappings between functions (operators) defined on complex computational domains is a common theoretical challenge in machine learning. Existing operator learning methods mainly focus on regular computational domains, and have many components ...
Chen Gengxiang +5 more
doaj +1 more source
Mathematics, 2021 In this work, we began to take forward kinematics of the Gough–Stewart (G-S) platform as an unconstrained optimization problem on the Lie group-structured manifold SE(3) instead of simply relaxing its intrinsic orthogonal constraint when algorithms are ...
Binhai Xie, Shuling Dai, Feng Liu
doaj +1 more source
Expectation Values and Variance Based on Lp-Norms
Entropy, 2012 This analysis introduces a generalization of the basic statistical concepts of expectation values and variance for non-Euclidean metrics induced by Lp-norms.
George Livadiotis
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On the Euclidean Operator Radius and Norm
Iranian Journal of ScienceIn this paper, we show several bounds for the numerical radius of a Hilbert space operator in terms of the Euclidean operator norm. The obtained forms will enable us to find interesting refinements of celebrated results in the literature. Then, the $f$-operator radius, recently defined as a generalization of the Euclidean operator radius, will be ...
Sababheh, Mohammad +2 more
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Non-Galois cubic fields which are Euclidean but not norm-Euclidean [PDF]
Mathematics of Computation, 1996 Weinberger in 1973 has shown that under the Generalized Riemann Hypothesis for Dedekind zeta functions, an algebraic number field with infinite unit group is Euclidean if and only if it is a principal ideal domain. Using a method recently introduced by us, we give two examples of cubic fields which are Euclidean but not norm–Euclidean.
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Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif +17 more
wiley +1 more source
White Matter and Perivascular Imaging Changes in Alzheimer's Disease and Cerebral Amyloid Angiopathy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Peak‐width of skeletonized mean diffusivity (PSMD) and diffusion tensor imaging–analysis along the perivascular space (DTI‐ALPS), reflecting white matter integrity and glymphatic function, are altered in Alzheimer's disease (AD).
Debina Laishram +3 more
wiley +1 more source
Diffusion Basis Spectrum Imaging of Tissue Microstructure and Early Treatment in Multiple Sclerosis
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Conventional MRI cannot resolve the coexisting pathological processes within multiple sclerosis tissue. Diffusion Basis Spectrum Imaging decomposes the diffusion signal into fiber, cell, and hindered ratios indexing axonal integrity, cellularity, and extracellular space, respectively.
Apisit Kaewsanit +10 more
wiley +1 more source
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +1 more source
Zone diagrams in Euclidean spaces and in other normed spaces [PDF]
Proceedings of the twenty-sixth annual symposium on Computational geometry, 2010 Title page + 16 pages, 20 ...
Akitoshi Kawamura +2 more
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