Zobrazeno 1 - 10
of 79
pro vyhledávání: '"Chang, Ziyi"'
Node Importance Estimation (NIE) is crucial for integrating external information into Large Language Models through Retriever-Augmented Generation. Traditional methods, focusing on static, single-graph characteristics, lack adaptability to new graphs
Externí odkaz:
http://arxiv.org/abs/2402.05135
Autor:
Chang, Ziyi
The size of the IoT network is expanding due to advancements in the IoT field, leading to increased interest in the multi-sink mechanism. The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is a representative IoT protocol that focuses o
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-329339
Recently, methods for skeleton-based human activity recognition have been shown to be vulnerable to adversarial attacks. However, these attack methods require either the full knowledge of the victim (i.e. white-box attacks), access to training data (
Externí odkaz:
http://arxiv.org/abs/2308.05681
Diffusion models are generative models, which gradually add and remove noise to learn the underlying distribution of training data for data generation. The components of diffusion models have gained significant attention with many design choices prop
Externí odkaz:
http://arxiv.org/abs/2306.04542
Generating realistic motions for digital humans is a core but challenging part of computer animations and games, as human motions are both diverse in content and rich in styles. While the latest deep learning approaches have made significant advancem
Externí odkaz:
http://arxiv.org/abs/2212.08526
Acquiring the virtual equivalent of exhibits, such as sculptures, in virtual reality (VR) museums, can be labour-intensive and sometimes infeasible. Deep learning based 3D reconstruction approaches allow us to recover 3D shapes from 2D observations,
Externí odkaz:
http://arxiv.org/abs/2210.04265
Generating realistic motions for digital humans is time-consuming for many graphics applications. Data-driven motion synthesis approaches have seen solid progress in recent years through deep generative models. These results offer high-quality motion
Externí odkaz:
http://arxiv.org/abs/2209.14828
Autor:
Zhao, Yang, Liu, Yuhao, Zhao, Guizhen, Lu, Haocheng, Liu, Yaozhong, Xue, Chao, Chang, Ziyi, Liu, Hongyu, Deng, Yongjie, Liang, Wenying, Wang, Huilun, Rom, Oren, Garcia-Barrio, Minerva T., Zhu, Tianqing, Guo, Yanhong, Chang, Lin, Lin, Jiandie, Chen, Y. Eugene, Zhang, Jifeng
Publikováno v:
In Cell Reports 31 October 2023 42(10)
Akademický článek
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Autor:
Chang, Ziyi1 (AUTHOR), Liu, Jixiang2,3,4 (AUTHOR), Wang, Bei1 (AUTHOR), Zhang, Honglei1 (AUTHOR), Zhao, Ling1 (AUTHOR), Su, Yunchao1 (AUTHOR), Xie, Wanmu2,3 (AUTHOR), Huang, Qiang2,3 (AUTHOR), Zhen, Yanan5 (AUTHOR), Lin, Fan5 (AUTHOR), Liu, Min6 (AUTHOR), Gao, Qian2,3 (AUTHOR), Pang, Wenyi2,3,4 (AUTHOR), Zhang, Zhu2,3 (AUTHOR), Tian, Han2,3,4 (AUTHOR), Li, Yishan2,3,7 (AUTHOR), Yang, Peiran3,8 (AUTHOR), Zhai, Zhenguo2,3,4 (AUTHOR) zhaizhenguo2011@126.com, Zhong, Dingrong1 (AUTHOR) zhaizhenguo2011@126.com
Publikováno v:
Journal of Clinical Medicine. Nov2022, Vol. 11 Issue 22, p6659. 11p.