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相关概念视频

Vector Algebra: Graphical Method01:10

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Vectors can be multiplied by scalars, added to other vectors, or subtracted from other vectors. The vector sum of two (or more) vectors is called the resultant vector or, for short, the resultant.
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Learning to draw Fischer projections of molecules and understanding their relevance plays a crucial role in the visual depiction of organic molecules. A Fischer projection is a two-dimensional projection on a planar surface to simplify the three-dimensional wedge–dash representation of molecules. This is especially helpful in the case of molecules with multiple chiral centers that can be difficult to draw. Here, all the bonds of interest are represented as horizontal or vertical lines.
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An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, the cumulative percentages are added to the graph from left to right. An ogive graph plots cumulative frequency on the vertical y-axis and class boundaries along the horizontal x-axis. It’s very similar to a histogram; only instead of rectangles, an ogive displays a single point where the top right of the rectangle would be. Creating this...
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The first order operators using the del operator include the gradient, divergence and curl. Certain combinations of first order operators on a scalar or vector function yield second order expressions. Second-order expressions play a very important role in mathematics and physics. Some second order expressions include the divergence and curl of a gradient function, the divergence and curl of a curl function, and the gradient of a divergence function.
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Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients
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DGHSA:基于衍生图的超图结构攻击衍生图.

Yang Chen1,2,3, Zhonglin Ye4,5, Zhaoyang Wang4,5

  • 1School of Computer Science and Technology, Shandong Technology and Business University, Yantai, 264005, Shandong, China. 202414305@sdtbu.edu.cn.

Scientific reports
|December 5, 2024
PubMed
概括
此摘要是机器生成的。

这项研究介绍了DGHSA,这是一种针对高图神经网络 (HGNN) 的新型非目标攻击方法. 通过优化超图扰动,DGHSA有效地降低了HGNN在节点分类上的性能.

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科学领域:

  • 人工智能的人工智能
  • 机器学习 机器学习
  • 数据科学数据科学数据科学

背景情况:

  • 超图神经网络 (HGNN) 擅长执行更高级别的任务,但容易受到对抗性攻击.
  • 目前对HGNN的攻击主要集中在有针对性的场景上,缺乏实际的非有针对性的策略.

研究的目的:

  • 为未定位的对抗场景提出一种新的基于导数图的超图攻击 (DGHSA).
  • 解决HGNN对降低全球性能的攻击的脆弱性.

主要方法:

  • DGHSA采用两阶段的方法:候选人集合生成和评估.
  • 来自训练有素的HGNN的梯度为攻击生成提供了超图结构修改的信息.
  • 一个导数图表度量评估节点相似性,以确定最佳扰动.

主要成果:

  • 在四个数据集上进行了广泛的实验,证明了DGHSA的有效性.
  • 拟议的攻击显著降低了HGNN在节点分类任务中的性能.
  • DGHSA成功地降低了HGNN的全球性能.

结论:

  • DGHSA提出了一种实用且有效的方法,用于对HGNNs进行无针对性的对抗性攻击.
  • 基于导数图的方法为分析HGNN强度提供了新的视角.
  • 进一步的研究可以探索对这种非目标的超图形攻击的防御.