CFGExplainer分为初始学习(Initial Learning)和解释(Interpretation)两个阶段。 从设计方案中直观来看CFGExplainer的优势在于:初始学习阶段,CFGExplainer的节点评分组件使用了来自不同ACFG样本的信息,即全局信息,因此可以泛化学习到同一类ACFG中的相似模式。另外,CFGExplainer利用ACFG中节点固有的重要性来完成解释任务。相比起来...
Such a model needs to encompass three stages of the visualization pipeline: encoding, decoding and interpretation. The encoding details how data are transformed into a visualization and what can be seen in the visualization. The decoding explains how humans construct graphical contexts inside the ...
4.3 The Interpretation Mechanism of GSATGSAT 的可解释性本质上来自于信息控制:GSAT通过注意向 GSGS 中注入随机性来减少输入图中的信息。在训练中,Eq.9Eq.9 中的正则项将尝试为所有边缘分配较大的随机性,但在分类损失 min−I(GS;Y)min−I(GS;Y)(相当于交叉熵损失)的驱动下,GSAT 可以学习减少在任务...
Graph Theory and related computational techniques have been applied to a wide range of problems in process design and analysis to facilitate visualization, formulation, computation and interpretation. These applications are illustrated with selected examples. Most problems of practical importance are of such...
Understanding wherestudents, both science and non‐science majors, specifically struggle in their ability to interpret graphical data would allow educators to adjust their pedagogy to bridge this potential gap between non‐scientific versus scientific data interpretation. 展开 ...
On understanding variability in data: a study of graph interpretation in an advanced experimental biology laboratory 来自 Semantic Scholar 喜欢 0 阅读量: 22 作者:WM Roth,S Temple 摘要: Data analysis is constitutive of the discovery sciences. Few studies in mathematics education, however, investigate...
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Matrix factorization techniques have been frequently applied in information retrieval, computer vision, and pattern recognition. Among them, Nonnegative Matrix Factorization (NMF) has received considerable attention due to its psychological and physiological interpretation of naturally occurring data whose repres...
While the former approach is the basis for most analyses of single-cell data, the latter enables a better interpretation of continuous phenotypes and processes such as development, dose response, and disease progression. Here, we unify both viewpoints. A central example of dissecting heterogeneity ...
Cancer is rarely the straightforward consequence of an abnormality in a single gene, but rather reflects a complex interplay of many genes, represented as gene modules. Here, we leverage the recent advances of model-agnostic interpretation approach and d