Abstract: Counterfactual subgraphs explain graph neural networks (GNNs) by answering the question: “How would the prediction change if a certain subgraph were absent in the input instance?” The ...
Abstract: Graph signal processing is an emerging field which aims to model processes that exist on the nodes of a network and are explained through diffusion over this structure. Graph signal ...
(C1) The output should contain only those NxN patterns of pixels that are present in the input. (Weak C2) Distribution of NxN patterns in the input should be similar to the distribution of NxN ...
What is a Gaussian Graphical Model ? A Gaussian graphical model captures conditional (in)dependencies among a set of variables. These are pairwise relations (partial correlations) controlling for the ...
1 Department of Computer Science and Engineering, Jahangirnagar University, Dhaka, Bangladesh. 2 Brandenburg University of Technology Cottbus-Senftenberg, Cottbus, Germany. A social network refers to ...
The Amazon rainforests are of critical importance for global climate regulation. However, there are concerns about the forest’s resilience. Understanding how negative shocks in one region can trigger ...
The accurate prediction of electricity prices has great significance for the power system and the electricity market, regional electricity prices are difficult to predict due to congestion issues in ...
Urban transportation destination prediction is a crucial issue in the area of intelligent transportation, such as urban traffic planning and traffic congestion control. The spatial structure of the ...
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