Results 81 to 90 of about 50,655 (282)

Numerical technique for solving physical models using reproducing kernel Hilbert space method with purely integral conditions

Boundary Value Problems
In this work, we investigate the Klein–Gordon equation, a physical problem, using the reproducing kernel Hilbert space method (RKHSM). The analytical solution is expressed as a series within the reproducing kernel Hilbert space (RKHS).
Hadjer Zerouali, Nourhane Attia, Ali Akgül, Ahcene Merad, Douha Saadi, Evren Hincal, Murad Khan Hassani   +6 more
doaj   +1 more source

BACH, a Bayesian Optimization Protocol for Accurate Coarse‐Grained Parameterization of Organic Liquids

Advanced Functional Materials, EarlyView.
We present a fully automated Bayesian optimization (BO) protocol for the parameterization of nonbonded interactions in coarse‐grain CG force fields (BACH). Using experimental thermophysical data, we apply the protocol to a broad range of liquids, spanning linear, branched, and unsaturated hydrocarbons, esters, triglycerides, and water.
Janak Prabhu, Akhil Pratap Singh, Pablo Campomanes, Stefano Vanni   +3 more
wiley   +1 more source

Numerical Solution of Nonlinear Advection Equation Using Reproducing Kernel Method

Journal of Mathematical Sciences and Modelling
In this study, an iterative approximation is proposed by using the reproducing kernel method (RKM) for the nonlinear advection equation. To apply the iterative RKM, specific reproducing kernel spaces are defined and their kernel functions are presented ...
Onur Saldır
doaj   +1 more source

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

Uniform Function Estimators in Reproducing Kernel Hilbert Spaces

, 2021
This paper addresses the problem of regression to reconstruct functions, which are observed with superimposed errors at random locations. We address the problem in reproducing kernel Hilbert spaces. It is demonstrated that the estimator, which is often derived by employing Gaussian random fields, converges in the mean norm of the reproducing kernel ...
Dommel, Paul, Pichler, Alois
openaire   +2 more sources

Computing Functions of Random Variables via Reproducing Kernel Hilbert Space Representations

, 2015
We describe a method to perform functional operations on probability distributions of random variables. The method uses reproducing kernel Hilbert space representations of probability distributions, and it is applicable to all operations which can be ...
Fukumizu, K., Harmeling, S., Muandet, K., Peters, J., Schölkopf, B.   +4 more
core   +1 more source

Triply‐Twinned Metamaterials: Unraveling the Mechanics and Failure Pathways Through High‐Resolution XCT

Advanced Materials, EarlyView.
Triply‐twinned architected lattices transform deformation from bending to stretching of struts, delivering up to threefold increases in stiffness and strength across polymeric and metallic systems. High‐resolution synchrotron XCT and image‐based simulations reveal how meta‐grain architecture, defects, and AM build orientation govern failure pathways ...
David McArthur, George Maddison, Jaianth Vijayakumar, Paul Tafforeau, Kathy Christofidou, Peter David Lee, PJ Tan, Chu Lun Alex Leung   +7 more
wiley   +1 more source

ML-ANet: A Transfer Learning Approach Using Adaptation Network for Multi-label Image Classification in Autonomous Driving

Chinese Journal of Mechanical Engineering, 2021
To reduce the discrepancy between the source and target domains, a new multi-label adaptation network (ML-ANet) based on multiple kernel variants with maximum mean discrepancies is proposed in this paper.
Guofa Li, Zefeng Ji, Yunlong Chang, Shen Li, Xingda Qu, Dongpu Cao   +5 more
doaj   +1 more source

Self‐Powered Flexible Triboelectric‐Gated Ion‐Gel Transistor for Neuromorphic Tactile Sensing and Human Activity Recognition

Advanced Materials, EarlyView.
A fully flexible ion‐gel‐gated graphene‐channel transistor driven by a triboelectric nanogenerator enables self‐powered tactile sensing and synaptic learning. Mimicking spike‐rate‐dependent plasticity, the device exhibits frequency‐selective potentiation and depression, supporting rate‐coded neuromorphic computation even under flex.
Hanseong Cho, Seoyeon Park, Youngmin Lee, Sejoon Lee   +3 more
wiley   +1 more source

Some Notes on Error Analysis for Kernel Based Regularized Interpolation

International Journal of Analysis and Applications, 2020
Kernel based regularized interpolation is one of the most important methods for approximating functions. The theory behind the kernel based regularized interpolation is the well-known Representer Theorem, which shows the form of approximation function in
Qing Zou
doaj