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相关概念视频

Neural Circuits01:25

Neural Circuits

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Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
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Time-Series Graph00:54

Time-Series Graph

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A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
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Work is done on an object when energy is transferred to the object. In other words, work is done when a force acts on a body that undergoes a displacement from one position to another. By definition, the work done by a force is the integral of the force with respect to the displacement along its path. Forces can vary as a function of position, and displacements can occur along various paths between two points. The magnitude of a force multiplied by the cosine of the angle that the force makes...
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Animal organs and organ systems constantly adjust to internal and external changes through a process called homeostasis ("steady state"). Examples of these changes include regulation of the level of glucose or calcium in the blood or internal responses to external temperatures. Homeostasis requires  maintaining an internal dynamic equilibrium:
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A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
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Long-term depression, or LTD, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTD is the process of synaptic weakening that occurs over time between pre and postsynaptic neuronal connections. The synaptic weakening of LTD works in opposition to synaptic strengthening by long-term potentiation (LTP) and together are the main mechanisms that underlie learning and memory.
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对时间网络的课程负面挖掘.

Ziyue Chen1, Tongya Zheng2, Mingli Song3

  • 1Department of Economics, University of California, Berkeley, Berkeley, CA, United States.

Neural networks : the official journal of the International Neural Network Society
|July 17, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了课程负挖矿 (CurNM),这是一个用于训练时间图神经网络 (TGNN) 的新框架. CurNM有效地解决了负采样方面的挑战,显著提高了TGNN对时间网络数据的性能.

关键词:
课程学习学习课程学习脱离纠的学习学习.负采样采集 负采样采集时间图神经网络的神经网络

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科学领域:

  • 图形神经网络的神经网络
  • 机器学习 机器学习
  • 网络科学 网络科学

背景情况:

  • 时间网络模拟动态交互,对社交和电子商务应用至关重要.
  • 现有的时间图神经网络 (TGNN) 专注于模型架构,忽视了负样本质量.
  • 在TGNN中,负采样面临着正稀疏性和正转移等挑战.

研究的目的:

  • 引入课程负采矿 (CurNM),通过提高负样品质量来增强TGNN培训的框架.
  • 为应对时间网络数据固有的积极稀疏性和积极转移挑战.
  • 开发一种强大且适应性强的方法来选择信息性的负样本.

主要方法:

  • 课程负挖矿 (CurNM) 框架采用模式意识的课程学习.
  • 动态更新的负池平衡随机,历史和硬负数.
  • 具有时间意识的负选择模块和回火随机负面以获得稳定的训练.

主要成果:

  • 在12个数据集和3个TGNN架构中,CurNM显著优于基线方法.
  • 除研究和参数灵敏度分析证实了该方法的有效性和稳定性.
  • 该方法成功地解决了时间网络培训中的积极稀疏性和积极转变.

结论:

  • 课程负采矿 (CurNM) 提供了一个强大的解决方案,用于TGNN的负采样.
  • 拟议的框架提高了临时网络的代表性质量和培训稳定性.
  • 这项工作在时间图神经网络领域取得了重大进展.