Zobrazeno 1 - 10
of 2 531
pro vyhledávání: '"li, Mengyao"'
With 3D Gaussian Splatting (3DGS) advancing real-time and high-fidelity rendering for novel view synthesis, storage requirements pose challenges for their widespread adoption. Although various compression techniques have been proposed, previous art s
Externí odkaz:
http://arxiv.org/abs/2410.08017
Autor:
Wang, Chong, Li, Mengyao, He, Junjun, Wang, Zhongruo, Darzi, Erfan, Chen, Zan, Ye, Jin, Li, Tianbin, Su, Yanzhou, Ke, Jing, Qu, Kaili, Li, Shuxin, Yu, Yi, Liò, Pietro, Wang, Tianyun, Wang, Yu Guang, Shen, Yiqing
Recent breakthroughs in large language models (LLMs) offer unprecedented natural language understanding and generation capabilities. However, existing surveys on LLMs in biomedicine often focus on specific applications or model architectures, lacking
Externí odkaz:
http://arxiv.org/abs/2409.00133
As an important and practical way to obtain high dynamic range (HDR) video, HDR video reconstruction from sequences with alternating exposures is still less explored, mainly due to the lack of large-scale real-world datasets. Existing methods are mos
Externí odkaz:
http://arxiv.org/abs/2405.00244
Publikováno v:
Journal of Medical Internet Research, Vol 22, Iss 11, p e20656 (2020)
BackgroundThe outbreak of COVID-19 began in 2019 and is expected to impact the psychological health of college students. Few studies have investigated the associations among health risk communication, social media, and psychological symptoms during a
Externí odkaz:
https://doaj.org/article/228f79c907bc459f800e2e0b56dc07e8
Autor:
Adra, Aya, Li, Mengyao
Publikováno v:
Resistance to Repression and Violence: Global Psychological Perspectives.
Externí odkaz:
https://doi.org/10.1093/9780197687703.003.0004
Thriving underwater applications demand efficient extreme compression technology to realize the transmission of underwater images (UWIs) in very narrow underwater bandwidth. However, existing image compression methods achieve inferior performance on
Externí odkaz:
http://arxiv.org/abs/2308.08721
Autor:
Ren, Jianxiong, Zhang, Xiaoming, Si, Xingyong, Kong, Xiangjun, Cong, Jinyu, Wang, Pingping, Li, Xiang, Zhang, Qianru, Yao, Peifen, Li, Mengyao, Cai, Yuanqi, Sun, Zhaocai, Liu, Kunmeng, Wei, Benzheng
mRNA therapy is gaining worldwide attention as an emerging therapeutic approach. The widespread use of mRNA vaccines during the COVID-19 outbreak has demonstrated the potential of mRNA therapy. As mRNA-based drugs have expanded and their indications
Externí odkaz:
http://arxiv.org/abs/2303.00288
A crucial assumption underlying the most current theory of machine learning is that the training distribution is identical to the test distribution. However, this assumption may not hold in some real-world applications. In this paper, we develop a le
Externí odkaz:
http://arxiv.org/abs/2302.04438
Autor:
Li, Jitao, Yue, Zhen, Li, Jie, Zheng, Chenglong, Yang, Dingyu, Wang, Silei, Li, Mengyao, Zhang, Yating, Yao, Jianquan
Terahertz (THz) chirality pursues customizable manipulation from narrowband to broadband. While conventional THz chirality is restricted by non-negligible linewidth and unable to handle narrowband well. Recently, the concept "quasi bound states in co
Externí odkaz:
http://arxiv.org/abs/2206.02486
Distributed sparse learning for high dimensional parameters has attached vast attentions due to its wide application in prediction and classification in diverse fields of machine learning. Existing distributed sparse regression usually takes an avera
Externí odkaz:
http://arxiv.org/abs/2206.02204