Results 81 to 90 of about 1,606 (181)
Journal of Function Spaces, 2015 We apply the reproducing kernel Hilbert space (RKHS) method for getting analytical and approximate solutions for second-order hyperbolic integrodifferential equations with a weighted integral condition.
A. Guezane-Lakoud +2 more
doaj +1 more source
Unsupervised Domain Adaptation by Mapped Correlation Alignment
IEEE Access, 2018 The goal of unsupervised domain adaptation aims to utilize labeled data from source domain to annotate the target-domain data, which has none of the labels.
Yun Zhang +3 more
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Medical Physics, Volume 53, Issue 8, August 2026.Abstract Background Speckle patterns in ultrasound images often obscure anatomical details, leading to diagnostic uncertainty. Recently, various deep learning‐based techniques have been introduced to effectively suppress speckle; however, their high computational costs pose challenges for low‐resource devices, such as portable ultrasound systems ...
Hyunwoo Cho +4 more
wiley +1 more source
Finite‐Block Polynomial and Volterra Structure in Reservoir Computing
Numerical Linear Algebra with Applications, Volume 33, Issue 4, August 2026.ABSTRACT Reservoir computing is analyzed through the algebraic structure generated by finite‐width reservoirs on fixed input blocks. For linear and quadratic logistic activations, the induced input‐to‐state map admits an exact finite Volterra representation, yielding an explicit characterization of the associated hypothesis class.
Alfio Borzì
wiley +1 more source
Journal of Taibah University for Science, 2019 In this work, the boundary layer flow of a Powell–Eyring non-Newtonian fluid over a stretching sheet has been investigated by a reproducing kernel method. Reproducing kernel functions are used to obtain the solutions.
Ali Akgül
doaj +1 more source
Climate change and crop resilience: harnessing metabolomics for predicting stress tolerance
New Phytologist, Volume 251, Issue 3, Page 975-995, August 2026.Summarised methodology for metabolite biomarker discovery and genomic targets selection for those metabolites to predict high‐throughput phenotypic and agronomic traits of interest for direct uptake in breeding programmes. Summary Global warming is driving climate change to levels not experienced since the advent of agriculture, primarily due to ...
Agyeya Pratap +3 more
wiley +1 more source
, 2016 To the best of our knowledge, there are no general well-founded robust methods for statistical unsupervised learning. Most of the unsupervised methods explicitly or implicitly depend on the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO).
Alam, Md. Ashad +2 more
openaire +2 more sources
Reproducing kernel Hilbert space methods for modelling the discount curve
We consider the theory of bond discounts, defined as the difference between the terminal payoff of the contract and its current price. Working in the setting of finite-dimensional realizations in the HJM framework, under suitable notions of no-arbitrage, the admissible discount curves take the form of polynomial, exponential functions.
Celary, Andreas +2 more
openaire +2 more sources
A numerical approach for solving the high-order nonlinear singular Emden–Fowler type equations
Advances in Difference Equations, 2018 Reproducing kernel Hilbert space method (RKHSM) is an analytical technique, which can overcome the difficulty at the singular point of non-homogeneous, linear singular initial value problems; especially when the singularity appears on the right-hand side
Atta Dezhbord +2 more
doaj +1 more source
Entropy Measures for Stochastic Processes with Applications in Functional Anomaly Detection
Entropy, 2018 We propose a definition of entropy for stochastic processes. We provide a reproducing kernel Hilbert space model to estimate entropy from a random sample of realizations of a stochastic process, namely functional data, and introduce two approaches to ...
Gabriel Martos +3 more
doaj +1 more source