Zobrazeno 1 - 10
of 1 036
pro vyhledávání: '"Chen Yutong"'
Publikováno v:
Advances in Nonlinear Analysis, Vol 12, Iss 1, Pp 349-381 (2023)
In this article, we study a class of nonlinear fractional Laplace problems with a parameter and superlinear nonlinearity (−Δ)su=λu+f(x,u),inΩ,u=0,inRN\Ω.\left\{\phantom{\rule[-1.25em]{}{0ex}}\begin{array}{ll}{\left(-\Delta )}^{s}u=\lambda u+f\l
Externí odkaz:
https://doaj.org/article/29c8125e9a9e4ca5ad1d7493b452c3ac
Publikováno v:
E3S Web of Conferences, Vol 490, p 03004 (2024)
Vertical greening is one of the effective measures to improve the microclimate and air quality of high-density urban street canyons, and its impact on the thermal environment is closely related to the street canyon morphology. In this paper, based on
Externí odkaz:
https://doaj.org/article/bf57321debc74d6fa53c8c53580777f1
3D Gaussian Splatting (3DGS) has recently transformed photorealistic reconstruction, achieving high visual fidelity and real-time performance. However, rendering quality significantly deteriorates when test views deviate from the camera angles used d
Externí odkaz:
http://arxiv.org/abs/2411.06390
This paper presents a natural generalisation of Saxl conjecture from a Lie-theoretical perspective, which is verified for the exceptional types. For classical types, progress is made using spin representations, revealing connections to certain tensor
Externí odkaz:
http://arxiv.org/abs/2409.17540
Autor:
Wei, Lai, Ying, Zhen, He, Muyang, Chen, Yutong, Yang, Qian, Hong, Yanzhe, Lu, Jiaping, Li, Xiaoying, Huang, Weiran, Chen, Ying
Diabetes is a chronic disease that poses a significant global health burden, and optimizing diabetes management requires multi-stakeholder collaboration. Large language models (LLMs) have shown promise in various healthcare scenarios, but their effec
Externí odkaz:
http://arxiv.org/abs/2409.13191
Time Series Anomaly Detection (TSAD) finds widespread applications across various domains such as financial markets, industrial production, and healthcare. Its primary objective is to learn the normal patterns of time series data, thereby identifying
Externí odkaz:
http://arxiv.org/abs/2406.19770
In the rapidly evolving field of artificial intelligence, large language models (LLMs) have emerged as powerful tools for a myriad of applications, from natural language processing to decision-making support systems. However, as these models become i
Externí odkaz:
http://arxiv.org/abs/2406.04428
In this paper, we investigate dynamic feature selection within multivariate time-series scenario, a common occurrence in clinical prediction monitoring where each feature corresponds to a bio-test result. Many existing feature selection methods fall
Externí odkaz:
http://arxiv.org/abs/2405.19729
Hazy images degrade visual quality, and dehazing is a crucial prerequisite for subsequent processing tasks. Most current dehazing methods rely on neural networks and face challenges such as high computational parameter pressure and weak generalizatio
Externí odkaz:
http://arxiv.org/abs/2404.15638
Neural rendering techniques have significantly advanced 3D human body modeling. However, previous approaches often overlook dynamics induced by factors such as motion inertia, leading to challenges in scenarios like abrupt stops after rotation, where
Externí odkaz:
http://arxiv.org/abs/2403.19160