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pro vyhledávání: '"Jia, Nan"'
We provided a comprehensive study of the properties of the black hole in the low-mass X-ray binary system 4U 1543-47, specifically focusing on the 2021 outburst (MJD 59380-59470). Using observations from the \textit{Insight}-HXMT mission, we employed
Externí odkaz:
http://arxiv.org/abs/2406.16292
Semi-supervised symmetric non-negative matrix factorization (SNMF) utilizes the available supervisory information (usually in the form of pairwise constraints) to improve the clustering ability of SNMF. The previous methods introduce the pairwise con
Externí odkaz:
http://arxiv.org/abs/2405.02688
Missing value imputation is a crucial preprocessing step for many machine learning problems. However, it is often considered as a separate subtask from downstream applications such as classification, regression, or clustering, and thus is not optimiz
Externí odkaz:
http://arxiv.org/abs/2405.00182
Standard Large Language Models (LLMs) struggle with handling dialogues with long contexts due to efficiency and consistency issues. According to our observation, dialogue contexts are highly structured, and the special token of \textit{End-of-Utteran
Externí odkaz:
http://arxiv.org/abs/2403.08312
Manipulating photon states serves as a primary requirement for various optical devices and is of high relevance for quantum information technology. Nevertheless, the fundamental theoretical framework for tens-of-photon states has not been established
Externí odkaz:
http://arxiv.org/abs/2311.16599
Autor:
Jia, Nan1 (AUTHOR) nan.jia@marshall.usc.edu, Luo, Xueming2 (AUTHOR) Xueming.Luo@temple.edu, Fang, Zheng3 (AUTHOR) 149281891@qq.com, Liao, Chengcheng3 (AUTHOR) 823912149@qq.com
Publikováno v:
Academy of Management Journal. Feb2024, Vol. 67 Issue 1, p5-32. 28p.
We report the results of fitting Insight-HXMT data to the black hole X-ray binary MAXI J1348-430, which was discovered on January 26th, 2019, with the Gas Slit Camera (GSC) on-board MAXI. Several observations at the beginning of the first burst were
Externí odkaz:
http://arxiv.org/abs/2309.05232
Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code -- supporting symbolic, graph-based Deep Neural Netw
Externí odkaz:
http://arxiv.org/abs/2308.11785
Autor:
Jia, Nan
Titre de l'écran-titre (visionné le 6 novembre 2023)
Les dispositifs microfluidiques exploitent les propriétés chimiques et physiques des gaz et des liquides à l'échelle microscopique. Comparés aux systèmes à l'échelle macroscopique, l
Les dispositifs microfluidiques exploitent les propriétés chimiques et physiques des gaz et des liquides à l'échelle microscopique. Comparés aux systèmes à l'échelle macroscopique, l
Externí odkaz:
http://hdl.handle.net/20.500.11794/128624