Zobrazeno 1 - 10
of 21 986
pro vyhledávání: '"An, Siwei"'
Graph Neural Networks (GNNs) with equivariant properties have achieved significant success in modeling complex dynamic systems and molecular properties. However, their expressiveness ability is limited by: (1) Existing methods often overlook the over
Externí odkaz:
http://arxiv.org/abs/2411.10000
Autor:
Chen, Zeyu, Wang, Enci, Zou, Hu, Zou, Siwei, Gao, Yang, Wang, Huiyuan, Yu, Haoran, Jia, Cheng, Li, Haixin, Ma, Chengyu, Yao, Yao, Ding, Weiyu, Zhu, Runyu
Understanding the circumgalactic medium (CGM) distribution of galaxies is the key to revealing the dynamical exchange of materials between galaxies and their surroundings. In this work, we use DESI EDR dataset to investigate the cool CGM of galaxies
Externí odkaz:
http://arxiv.org/abs/2411.08485
Early fault detection and timely maintenance scheduling can significantly mitigate operational risks in NPPs and enhance the reliability of operator decision-making. Therefore, it is necessary to develop an efficient Prognostics and Health Management
Externí odkaz:
http://arxiv.org/abs/2411.08370
Autor:
Zhao, Cheng, Huang, Song, He, Mengfan, Montero-Camacho, Paulo, Liu, Yu, Renard, Pablo, Tang, Yunyi, Verdier, Aurelien, Xu, Wenshuo, Yang, Xiaorui, Yu, Jiaxi, Zhang, Yao, Zhao, Siyi, Zhou, Xingchen, He, Shengyu, Kneib, Jean-Paul, Li, Jiayi, Li, Zhuoyang, Wang, Wen-Ting, Xianyu, Zhong-Zhi, Zhang, Yidian, Gsponer, Rafaela, Li, Xiao-Dong, Rocher, Antoine, Zou, Siwei, Tan, Ting, Huang, Zhiqi, Wang, Zhuoxiao, Li, Pei, Rombach, Maxime, Dong, Chenxing, Forero-Sanchez, Daniel, Shan, Huanyuan, Wang, Tao, Li, Yin, Zhai, Zhongxu, Wang, Yuting, Zhao, Gong-Bo, Shi, Yong, Mao, Shude, Huang, Lei, Guo, Liquan, Cai, Zheng
The MUltiplexed Survey Telescope (MUST) is a 6.5-meter telescope under development. Dedicated to highly-multiplexed, wide-field spectroscopic surveys, MUST observes over 20,000 targets simultaneously using 6.2-mm pitch positioning robots within a ~5
Externí odkaz:
http://arxiv.org/abs/2411.07970
Utilizing fault diagnosis methods is crucial for nuclear power professionals to achieve efficient and accurate fault diagnosis for nuclear power plants (NPPs). The performance of traditional methods is limited by their dependence on complex feature e
Externí odkaz:
http://arxiv.org/abs/2411.06765
The safe and reliable operation of complex electromechanical systems in nuclear power plants is crucial for the safe production of nuclear power plants and their nuclear power unit. Therefore, accurate and timely fault diagnosis of nuclear power syst
Externí odkaz:
http://arxiv.org/abs/2411.07453
Autor:
Raviv-Moshe, Avia, Zhong, Siwei
We study point impurities in non-relativistic quantum field theories, with a focus on scale-invariant fixed points. We establish the framework of conformal defects in Schr\"{o}dinger field theories and their correspondence to many-body states in a ha
Externí odkaz:
http://arxiv.org/abs/2411.04040
The rapid development of generative Artificial Intelligence (AI) continually unveils the potential of Semantic Communication (SemCom). However, current talking-face SemCom systems still encounter challenges such as low bandwidth utilization, semantic
Externí odkaz:
http://arxiv.org/abs/2411.03876
Meta-learning is a general approach to equip machine learning models with the ability to handle few-shot scenarios when dealing with many tasks. Most existing meta-learning methods work based on the assumption that all tasks are of equal importance.
Externí odkaz:
http://arxiv.org/abs/2410.18894
Autor:
Wu, Siwei, Peng, Zhongyuan, Du, Xinrun, Zheng, Tuney, Liu, Minghao, Wu, Jialong, Ma, Jiachen, Li, Yizhi, Yang, Jian, Zhou, Wangchunshu, Lin, Qunshu, Zhao, Junbo, Zhang, Zhaoxiang, Huang, Wenhao, Zhang, Ge, Lin, Chenghua, Liu, J. H.
Enabling Large Language Models (LLMs) to handle a wider range of complex tasks (e.g., coding, math) has drawn great attention from many researchers. As LLMs continue to evolve, merely increasing the number of model parameters yields diminishing perfo
Externí odkaz:
http://arxiv.org/abs/2410.13639