Zobrazeno 1 - 10
of 3 853
pro vyhledávání: '"Wang, Zhu A."'
Graph contrastive learning (GCL) has shown promising performance in semisupervised graph classification. However, existing studies still encounter significant challenges in GCL. First, successive layers in graph neural network (GNN) tend to produce m
Externí odkaz:
http://arxiv.org/abs/2411.15206
Autor:
Chen, Guang-Jie, Zhao, Dong, Wang, Zhu-Bo, Li, Ziqin, Zhang, Ji-Zhe, Chen, Liang, Zhang, Yan-Lei, Xu, Xin-Biao, Liu, Ai-Ping, Dong, Chun-Hua, Guo, Guang-Can, Huang, Kun, Zou, Chang-Ling
Precise control and manipulation of neutral atoms are essential for quantum technologies but largely dependent on conventional bulky optical setups. Here, we demonstrate a multifunctional metalens that integrates an achromatic lens with large numeric
Externí odkaz:
http://arxiv.org/abs/2411.05501
Autor:
Zhang, Yan-Lei, Jie, Qing-Xuan, Li, Ming, Wu, Shu-Hao, Wang, Zhu-Bo, Zou, Xu-Bo, Zhang, Peng-Fei, Li, Gang, Zhang, Tiancai, Guo, Guang-Can, Zou, Chang-Ling
Realizing large-scale quantum networks requires the generation of high-fidelity quantum entanglement states between remote quantum nodes, a key resource for quantum communication, distributed computation and sensing applications. However, entanglemen
Externí odkaz:
http://arxiv.org/abs/2410.12523
Autor:
Zhang, Mingjie, Feng, Chen, Li, Zengzhi, Zheng, Guiyong, Luo, Yiming, Wang, Zhu, Zhou, Jinni, Shen, Shaojie, Zhou, Boyu
Unmanned Aerial Vehicles (UAVs) have gained significant popularity in scene reconstruction. This paper presents SOAR, a LiDAR-Visual heterogeneous multi-UAV system specifically designed for fast autonomous reconstruction of complex environments. Our
Externí odkaz:
http://arxiv.org/abs/2409.02738
Autor:
Zhang, Yan-Lei, Li, Ming, Xu, Xin-Biao, Wang, Zhu-Bo, Dong, Chun-Hua, Guo, Guang-Can, Zou, Chang-Ling, Zou, Xu-Bo
The switching and control of optical fields based on nonlinear optical effects are often limited to relatively weak nonlinear susceptibility and strong optical pump fields. Here, an optical medium with programmable susceptibility tensor based on pola
Externí odkaz:
http://arxiv.org/abs/2409.01106
Autor:
Hu, Yuxiong, Hu, Jianyu, Sun, Mengzhao, Li, Aowen, Shi, Shucheng, Hu, P. J., Zhou, Wu, Willinger, Marc-Georg, Zhou, Dan, Liu, Zhi, Liu, Xi, Li, Wei-Xue, Wang, Zhu-Jun
The interplay between order and disorder is crucial across various fields, especially in understanding oscillatory phenomena. Periodic oscillations are frequently observed in heterogeneous catalysis, yet their underlying mechanisms need deeper explor
Externí odkaz:
http://arxiv.org/abs/2408.07374
Graph anomaly detection (GAD) has been widely applied in many areas, e.g., fraud detection in finance and robot accounts in social networks. Existing methods are dedicated to identifying the outlier nodes that deviate from normal ones. While they hea
Externí odkaz:
http://arxiv.org/abs/2407.05934
Recent advancements in Artificial Intelligence (AI) and machine learning have demonstrated transformative capabilities across diverse domains. This progress extends to the field of patent analysis and innovation, where AI-based tools present opportun
Externí odkaz:
http://arxiv.org/abs/2404.08668
Autor:
Chen, Guang-Jie, Wang, Zhu-Bo, Gu, Chenyue, Zhao, Dong, Zhang, Ji-Zhe, Zhang, Yan-Lei, Dong, Chun-Hua, Huang, Kun, Guo, Guang-Can, Zou, Chang-Ling
Single atoms trapped in tightly focused optical dipole traps provide an excellent experimental platform for quantum computing, precision measurement, and fundamental physics research. In this work, we propose and demonstrate a novel approach to enhan
Externí odkaz:
http://arxiv.org/abs/2403.03068
Publikováno v:
Computer Methods in Applied Mechanics and Engineering, Volume 427, 2024, 117033
Hamiltonian Operator Inference has been introduced in [Sharma, H., Wang, Z., Kramer, B., Physica D: Nonlinear Phenomena, 431, p.133122, 2022] to learn structure-preserving reduced-order models (ROMs) for Hamiltonian systems. This approach constructs
Externí odkaz:
http://arxiv.org/abs/2401.12138