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Heat Kernel Analysis of Syntactic Structures [PDF]
Mathematics in Computer Science, 2021 We consider two different data sets of syntactic parameters and we discuss how to detect relations between parameters through a heat kernel method developed by Belkin-Niyogi, which produces low dimensional representations of the data, based on Laplace eigenfunctions, that preserve neighborhood information.
Andrew Ortegaray +2 more
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Cogent Engineering, 2023 The Superheated steam has been shown to be more effective than hot air for drying corn. Modeling studies have been carried out in fluidized bed dryers to determine the moisture and heat transfer characteristics of corn, but there are no modeling studies ...
Mercy Jepchirchir Kimwa +2 more
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The Heat Kernel on Hyperbolic Space [PDF]
Bulletin of the London Mathematical Society, 1998 A new proof of the explicit formula for the heat kernel on hyperbolic space is provided. This formula is due to \textit{H. P. McKean} [J. Differ. Geom. 4, 359-366 (1970; Zbl 0197.18003)] for the case of the two-dimensional hyperbolic space and to \textit{A. Debiard, B. Gaveau} and \textit{E. Mazet} [Publ. Res. Inst. Math. Sci., Kyoto Univ. 12, 391-425 (
Grigor'yan, Alexander, Noguchi, Masakazu
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A Varadhan Estimate for Big Order Differential Generators
Computer Sciences & Mathematics Forum, 2023 We give a logarithmic estimate of an elliptic semi-group generated by a big-order generator by using the Malliavin Calculus of Bismut type and large deviation estimates.
Rémi Léandre
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Embeddings between Triebel-Lizorkin Spaces on Metric Spaces Associated with Operators
Analysis and Geometry in Metric Spaces, 2020 We consider the general framework of a metric measure space satisfying the doubling volume property, associated with a non-negative self-adjoint operator, whose heat kernel enjoys standard Gaussian localization.
Georgiadis Athanasios G. +1 more
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Heat Kernel Expansions on the Integers [PDF]
Mathematical Physics, Analysis and Geometry, 2002 18 ...
Grünbaum, F. Alberto, Iliev, Plamen
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Exact Heat Kernel on a Hypersphere and Its Applications in Kernel SVM
Frontiers in Applied Mathematics and Statistics, 2018 Many contemporary statistical learning methods assume a Euclidean feature space. This paper presents a method for defining similarity based on hyperspherical geometry and shows that it often improves the performance of support vector machine compared to ...
Chenchao Zhao +3 more
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Cones, spins and heat kernels [PDF]
Nuclear Physics B, 1997 The heat kernels of Laplacians for spin 1/2, 1, 3/2 and 2 fields, and the asymptotic expansion of their traces are studied on manifolds with conical singularities. The exact mode-by-mode analysis is carried out for 2-dimensional domains and then extended to arbitrary dimensions.
FURSAEV D. V, MIELE, GENNARO
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Adaptive Graph Convolution Using Heat Kernel for Attributed Graph Clustering
Applied Sciences, 2020 Attributed graphs contain a lot of node features and structural relationships, and how to utilize their inherent information sufficiently to improve graph clustering performance has attracted much attention.
Danyang Zhu +3 more
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Variable Besov–Morrey Spaces Associated with Operators
Mathematics, 2023 Let (X,d,μ) be a space of homogenous type and L be a non-negative self-adjoint operator on L2(X) with heat kernels satisfying Gaussian upper bounds. In this paper, we introduce the variable Besov–Morrey space associated with the operator L and prove that
Khedoudj Saibi
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