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Graph Modification for Edge-Coloured and Signed Graph Homomorphism Problems: Parameterized and Classical Complexity
We study the complexity of graph modification problems with respect to homomorphism-based colouring properties of edge-coloured graphs. A...
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Hardness of Bounding Influence via Graph Modification
We consider the problem of minimally modifying graphs and digraphs by way of exclusively deleting vertices, exclusively deleting edges, or...
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MDGCL: Graph Contrastive Learning Framework with Multiple Graph Diffusion Methods
In recent years, some classical graph contrastive learning(GCL) frameworks have been proposed to address the problem of sparse labeling of graph data...
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Modification-fair cluster editing
The classic Cluster Editing problem (also known as Correlation Clustering ) asks to transform a given graph into a disjoint union of cliques...
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The Polynomial Algorithm of Finding the Shortest Path in a Divisible Multiple Graph
AbstractIn this paper, we study undirected multiple graphs of any natural multiplicity k > 1. There are edges of three types: ordinary edges,...
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Large-scale knowledge graph representation learning
The knowledge graph emerges as powerful data structures that provide a deep representation and understanding of the knowledge presented in networks....
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Defense against membership inference attack in graph neural networks through graph perturbation
Graph neural networks have demonstrated remarkable performance in learning node or graph representations for various graph-related tasks. However,...
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SimGCL: graph contrastive learning by finding homophily in heterophily
Graph Contrastive learning (GCL) has been widely studied in unsupervised graph representation learning. Most existing GCL methods focus on modeling...
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OneGraph: a cross-architecture framework for large-scale graph computing on GPUs based on oneAPI
The explosive growth of graph data sets has led to an increase in the computing power and storage resources required for graph computing. To handle...
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Heterogeneous graph attention networks for passage retrieval
This paper presents an exploration of the usage of Heterogeneous Graph Attention Networks, or HGATs, for the task of Passage Retrieval. More...
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Protecting the privacy of social network data using graph correction
Today, the rapid development of online social networks, as well as low costs, easy communication, and quick access with minimal facilities have made...
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Graph partitioning and visualization in graph mining: a survey
Graph mining is a process of obtaining one or more sub-graphs and has been a very attractive research topic over the last two decades. It has found...
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Graph neural networks: a survey on the links between privacy and security
Graph neural networks (GNNs) are models that capture the dependencies between graph data by passing messages between graph nodes and they have been...
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Neural Graph Revealers
Sparse graph recovery methods work well where the data follows their assumptions, however, they are not always designed for doing downstream...
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Multi-graph embedding for partial label learning
Partial label learning (PLL) is an essential weakly supervised learning method. In PLL, the example’s ground-truth label is unknown and hidden in a...
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Towards High-Performance Graph Processing: From a Hardware/Software Co-Design Perspective
Graph processing has been widely used in many scenarios, from scientific computing to artificial intelligence. Graph processing exhibits irregular...
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DialGNN: Heterogeneous Graph Neural Networks for Dialogue Classification
Dialogue systems have attracted growing research interests due to its widespread applications in various domains. However, most research work focus...
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Method for the Adaptive Neutralization of Structural Breaches in Cyber-Physical Systems Based on Graph Artificial Neural Networks
AbstractThis paper presents a model of threats in cyber-physical systems (CPSs) with examples of attacks and potential negative consequences for...
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Dynamic graph neural network-based computational paradigm for video summarization
In recent times, there has been a significant amount of interest in video summary technology. The reason behind video summarizing is to condense the...
