Zobrazeno 1 - 10
of 13 093
pro vyhledávání: '"Zhao, JIN"'
In the field of finance, the prediction of individual credit default is of vital importance. However, existing methods face problems such as insufficient interpretability and transparency as well as limited performance when dealing with high-dimensio
Externí odkaz:
http://arxiv.org/abs/2411.17783
The high-index saddle dynamics (HiSD) method is a powerful approach for computing saddle points and solution landscape. However, its practical applicability is constrained by the need for the explicit energy function expression. To overcome this chal
Externí odkaz:
http://arxiv.org/abs/2411.16200
Autor:
Tang, Jia-Cheng, Zhao, Jin, Yang, Haitao, Tian, Junlong, Tang, Pinghua, Wang, Shuai-Peng, Lamata, Lucas, Peng, Jie
We propose a scheme for realizing a deterministic two-photon C-Z gate based on variants of the two-photon quantum Rabi model, which is feasible within the framework of circuit QED. We begin by utilizing the two-photon interaction to implement the non
Externí odkaz:
http://arxiv.org/abs/2411.03762
Extreme weather events can cause widespread power outages and huge economic losses. Low-income customers are more vulnerable to power outages because they live in areas with poorly equipped distribution systems. However, existing approaches to improv
Externí odkaz:
http://arxiv.org/abs/2410.13992
Autor:
Zhang, Yuxin, Lin, Zheng, Chen, Zhe, Fang, Zihan, Zhu, Wenjun, Chen, Xianhao, Zhao, Jin, Gao, Yue
Traditional federated learning (FL) frameworks rely heavily on terrestrial networks, where coverage limitations and increasing bandwidth congestion significantly hinder model convergence. Fortunately, the advancement of low-Earth orbit (LEO) satellit
Externí odkaz:
http://arxiv.org/abs/2409.13503
Network embedding has numerous practical applications and has received extensive attention in graph learning, which aims at mapping vertices into a low-dimensional and continuous dense vector space by preserving the underlying structural properties o
Externí odkaz:
http://arxiv.org/abs/2408.02705
Higher-order graph clustering aims to partition the graph using frequently occurring subgraphs. Motif conductance is one of the most promising higher-order graph clustering models due to its strong interpretability. However, existing motif conductanc
Externí odkaz:
http://arxiv.org/abs/2406.07357
Autor:
Zhu, Lingjun, Zheng, Qijing, Wang, Yingqi, Krüger, Kerstin, Wodtke, Alec M., Bünermann, Oliver, Zhao, Jin, Guo, Hua, Jiang, Bin
To understand the recently observed mysterious non-adiabatic energy transfer for hyperthermal H atom scattering from a semiconductor surface, Ge(111)c(2*8), we present a mixed quantum-classical non-adiabatic molecular dynamics model based on time-dep
Externí odkaz:
http://arxiv.org/abs/2405.13361
Federated Learning (FL) is a distributed learning scheme that enables deep learning to be applied to sensitive data streams and applications in a privacy-preserving manner. This paper focuses on the use of FL for analyzing smart energy meter data wit
Externí odkaz:
http://arxiv.org/abs/2404.03320
Recent advancements in Large Language Models (LLMs), particularly those built on Transformer architectures, have significantly broadened the scope of natural language processing (NLP) applications, transcending their initial use in chatbot technology
Externí odkaz:
http://arxiv.org/abs/2403.18969