Zobrazeno 1 - 10
of 677
pro vyhledávání: '"Xu, Liwei"'
Training deep neural networks is a challenging task. In order to speed up training and enhance the performance of deep neural networks, we rectify the vanilla conjugate gradient as conjugate-gradient-like and incorporate it into the generic Adam, and
Externí odkaz:
http://arxiv.org/abs/2404.01714
We develop a Macroscopic Auxiliary Asymptotic-Preserving Neural Network (MA-APNN) method to solve the time-dependent linear radiative transfer equations (LRTEs), which have a multi-scale nature and high dimensionality. To achieve this, we utilize the
Externí odkaz:
http://arxiv.org/abs/2403.01820
Few-shot learning for image classification comes up as a hot topic in computer vision, which aims at fast learning from a limited number of labeled images and generalize over the new tasks. In this paper, motivated by the idea of Fisher Score, we pro
Externí odkaz:
http://arxiv.org/abs/2305.08721
We propose a model-data asymptotic-preserving neural network(MD-APNN) method to solve the nonlinear gray radiative transfer equations(GRTEs). The system is challenging to be simulated with both the traditional numerical schemes and the vanilla physic
Externí odkaz:
http://arxiv.org/abs/2212.05523
Based on the perfectly matched layer (PML) technique, this paper develops a high-accuracy boundary integral equation (BIE) solver for acoustic scattering problems in locally defected layered media in both two and three dimensions. The original scatte
Externí odkaz:
http://arxiv.org/abs/2211.00892
Publikováno v:
Open Life Sciences, Vol 19, Iss 1, Pp 1592-9 (2024)
Neuroinflammation, characterized by microglial activation and the subsequent secretion of inflammatory cytokines, plays a pivotal role in neurodegenerative diseases and brain injuries, often leading to neuronal damage and death. Alleviating neuroinfl
Externí odkaz:
https://doaj.org/article/e8a379b0b7c34886aa641f67e1f21929
In this paper, we propose a stochastic Gauss-Newton (SGN) algorithm to study the online principal component analysis (OPCA) problem, which is formulated by using the symmetric low-rank product (SLRP) model for dominant eigenspace calculation. Compare
Externí odkaz:
http://arxiv.org/abs/2203.13081
In this paper, we propose and analyze a fully discrete finite element projection method for the magnetohydrodynamic (MHD) equations. A modified Crank--Nicolson method and the Galerkin finite element method are used to discretize the model in time and
Externí odkaz:
http://arxiv.org/abs/2203.07680
Autor:
Li, Lingyan, Xu, Liwei, Jia, Guangping, Zhou, Xiaoqin, Tang, Xin, Zhao, Han, Ma, Yuanyuan, Ma, Peifen, Chen, Jingjing
Publikováno v:
In Nurse Education Today October 2024 141
Publikováno v:
In Microelectronics Journal September 2024 151