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天津大学研究团队开创性地结合量子计算与隐式神经表征:量子隐式表征网络诞生

近日,天津大学量子智能与语言理解团队在学术领域掀起波澜,他们创新性地将量子计算引入隐式神经表征领域,提出了全新的量子隐式表征网络(Quantum Implicit Representation Network, QIREN)。这一突破性的研究由张鹏教授及其团队完成,得到了包括硕士生赵佳铭、博士生乔文博以及高珲的共同努力。

该团队的研究工作得到了国家自然科学基金委以及天津大学-中科闻歌联合实验室的资助。他们在研究中发现,与传统的经典神经网络方法相比,量子隐式表征网络在理论上具有指数级强的信号表征能力。这意味着在特定的计算任务中,量子计算的应用能大大提高信息的处理效率和准确性。

实验结果显示,该网络不仅在信号表征上表现出色,更在内存使用上展现了巨大的优势,其内存节省超过35%。论文链接https://arxiv.org/abs/2406.03873详细阐述了这一新兴的网络结构和相关理论。该论文也得到了机器之心AIxiv专栏的发布和推广,欢迎对此感兴趣的研究者进行学术交流与投稿。投稿邮箱为:liyazhou@jiqizhixin.com以及zhaoyunfeng@jiqizhixin.com。

这项研究不仅是学术界的一次重大突破,也为量子计算和人工智能的融合开辟了新的道路。未来,天津大学量子智能与语言理解团队的研究将可能引领量子计算技术在更多领域的应用和发展。

英语如下:

News Title: Tianjin University Makes a Breakthrough: Quantum Implicit Representation Network Shows Exponential Strong Signal Representation Ability

Keywords: 1. Quantum Implicit Representation Network

News Content:
Tianjin University research team combines quantum computing and implicit neural representation: Quantum Implicit Representation Network is born

Recently, the Tianjin University Quantum Intelligence and Language Understanding Team has caused a stir in the academic field. They have innovatively introduced quantum computing into the field of implicit neural representations, proposing a brand-new Quantum Implicit Representation Network (QIREN). This groundbreaking research was completed by Professor Zhang Peng and his team, including master’s student Zhao Jiaming, doctoral student Qiao Wenbo, and Gao Hui.

The team’s research work was funded by the National Natural Science Foundation of China and the Tianjin University-Zhongke Wenguan Joint Laboratory. In their research, they found that compared with traditional classical neural network methods, the Quantum Implicit Representation Network has theoretically exponential strong signal representation ability. This means that in specific computational tasks, the application of quantum computing can greatly improve information processing efficiency and accuracy.

Experimental results show that the network not only performs well in signal representation but also demonstrates a significant advantage in memory usage, with memory savings exceeding 35%. The paper link https://arxiv.org/abs/2406.03873 details this emerging network structure and related theories. The paper has also been published and promoted by the Machine ZhinXinAIxiv column. Researchers interested in this are welcome to conduct academic exchanges and submit papers to [liyazhou@jiqizhixin.com](mailto:liyazhou@jiqizhixin.com) and [zhaoyunfeng@jiqizhixin.com](mailto:zhaoyunfeng@jiqizhixin.com).

This research is not only a significant breakthrough in academia but also opens up new paths for the integration of quantum computing and artificial intelligence. In the future, the research of the Tianjin University Quantum Intelligence and Language Understanding Team may lead the application and development of quantum computing technology in more fields.

【来源】https://www.jiqizhixin.com/articles/2024-06-26-4

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