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Oct 14, 2022 · It is an efficient and useful post-hoc method for studying the interpretability of machine learning models without the need for expensive model ...
characterize the influence of graph elements to model parameters' changes, we consider a convex model called Simple Graph Convolution from the GCNs family.
Jan 25, 2023 · To introduce influence functions from i.i.d. data to graphs and precisely characterize the influence of graph elements to model parameters' ...
The influence function of an SGC model could be used to estimate the impact of removing training nodes/edges on the test performance of the SGC without ...
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Characterizing the Influence of Graph Elements. by Zizhang Chen, Hongfu Liu and Pengyu Hong. Date presented 05/03/2023. The International Conference on ...
We study the characterization of graphs which have an exact-distance square root within a particular graph class.
Missing: Elements. | Show results with:Elements.
Characterizing the Influence of Graph Elements · Revisiting Graph Adversarial Attack and Defense From a Data Distribution Perspective. Robustness. Revisiting ...
In mathematics and computer science, graph theory is the study of graphs, which are mathematical structures used to model pairwise relations between objects.
In this work, we will show how to trans- form scenes into a relationship graph whose nodes represent se- mantically meaningful objects or collections of objects ...
In the context of the present study, this implies that the descriptors of the Van Hiele levels for graphs should not contradict either the characteristics ...