Zobrazeno 1 - 10
of 3 657
pro vyhledávání: '"Wang, YunPeng"'
Transformer neural operators have recently become an effective approach for surrogate modeling of nonlinear systems governed by partial differential equations (PDEs). In this paper, we introduce a modified implicit factorized transformer (IFactFormer
Externí odkaz:
http://arxiv.org/abs/2412.18840
Acquisition of large datasets for three-dimensional (3D) partial differential equations are usually very expensive. Physics-informed neural operator (PINO) eliminates the high costs associated with generation of training datasets, and shows great pot
Externí odkaz:
http://arxiv.org/abs/2411.04502
Autor:
Zhang, Zhiyao, Li, Zhijie, Wang, Yunpeng, Yang, Huiyu, Peng, Wenhui, Teng, Jian, Wang, Jianchun
The accurate and fast prediction of long-term dynamics of turbulence presents a significant challenge for both traditional numerical simulations and machine learning methods. In recent years, the emergence of neural operators has provided a promising
Externí odkaz:
http://arxiv.org/abs/2411.01885
Rapid and accurate diagnosis of pneumothorax, utilizing chest X-ray and computed tomography (CT), is crucial for assisted diagnosis. Chest X-ray is commonly used for initial localization of pneumothorax, while CT ensures accurate quantification. Howe
Externí odkaz:
http://arxiv.org/abs/2407.15356
Fast and accurate predictions of turbulent flows are of great importance in the science and engineering field. In this paper, we investigate the implicit U-Net enhanced Fourier neural operator (IUFNO) in the stable prediction of long-time dynamics of
Externí odkaz:
http://arxiv.org/abs/2403.03051
The discrete direct deconvolution model (D3M) is developed for the large-eddy simulation (LES) of turbulence. The D3M is a discrete approximation of previous direct deconvolution model studied by Chang et al. ["The effect of sub-filter scale dynamics
Externí odkaz:
http://arxiv.org/abs/2402.08442
Autor:
Yao, Jincao, Wang, Yunpeng, Lei, Zhikai, Wang, Kai, Li, Xiaoxian, Zhou, Jianhua, Hao, Xiang, Shen, Jiafei, Wang, Zhenping, Ru, Rongrong, Chen, Yaqing, Zhou, Yahan, Chen, Chen, Zhang, Yanming, Liang, Ping, Xu, Dong
An artificial intelligence-generated content-enhanced computer-aided diagnosis (AIGC-CAD) model, designated as ThyGPT, has been developed. This model, inspired by the architecture of ChatGPT, could assist radiologists in assessing the risk of thyroid
Externí odkaz:
http://arxiv.org/abs/2402.02401
Macroscopic link-based flow models are efficient for simulating flow propagation in urban road networks. Existing link-based flow models described traffic states of a link with two state variables of link inflow and outflow and assumed homogeneous tr
Externí odkaz:
http://arxiv.org/abs/2310.12249
An ensemble Kalman filter (EnKF)-based mixed model (EnKF-MM) is proposed for the subgrid-scale (SGS) closure in the large-eddy simulation (LES) of turbulence. The model coefficients are determined through the EnKF-based data assimilation technique. T
Externí odkaz:
http://arxiv.org/abs/2305.11112
Traffic volume is an indispensable ingredient to provide fine-grained information for traffic management and control. However, due to limited deployment of traffic sensors, obtaining full-scale volume information is far from easy. Existing works on t
Externí odkaz:
http://arxiv.org/abs/2303.05660