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Random memristor-based dynamic graph CNN for efficient point cloud learning at the edge
The broad integration of 3D sensors into devices like smartphones and AR/VR headsets has led to a surge in 3D data, with point clouds becoming a...
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Unveiling the Interplay Between Degree-Based Graph Invariants of a Graph and Its Random Subgraphs
This paper investigates the significance of employing random subgraphs and analyzing the expected values of Zagreb ndices within chemical graphs. By...
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Sieve Methods in Random Graph Theory
In this paper, we apply the Turán sieve and the simple sieve developed by R. Murty and the first author to study problems in random graph theory. In...
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Hierarchical Bayesian adaptive lasso methods on exponential random graph models
The analysis of network data has become an increasingly prominent and demanding field across multiple research fields including data science, health,...
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Echo state graph neural networks with analogue random resistive memory arrays
Recent years have witnessed a surge of interest in learning representations of graph-structured data, with applications from social networks to drug...
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Approximating the Controllability Robustness of Directed Random-graph Networks Against Random Edge-removal Attacks
Network controllability robustness reflects how well a networked system can maintain its controllability against destructive attacks. Its performance...
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GRAPE for fast and scalable graph processing and random-walk-based embedding
Graph representation learning methods opened new avenues for addressing complex, real-world problems represented by graphs. However, many graphs used...
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Secure chaotic image encryption method using random graph traversal and three step diffusion
In this paper, we have presented an image encryption technique using random graph traversal, chaotic maps, and a secure hashing algorithm. Due to the...
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On the Distances Within Cliques in a Soft Random Geometric Graph
We study the distances of vertices within cliques in a soft random geometric graph on a torus, where the vertices are points of a homogeneous Poisson...
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A Note on the Markovian SIR Epidemic on a Random Graph with Given Degrees
We consider a Markovian model of an SIR epidemic spreading on a contact graph that is drawn uniformly at random from the set of all graphs with n ...
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The Optimal Pathin an Erdős-Rényi Random Graph
We study the optimal distance $\ell_{\mbox{\scriptsize opt}}$ in...
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RW-HeCo: A random walk and network centrality based graph neural network for community detection in heterogeneous networks
Real-world networks often consist of different types of nodes, which leads to the creation of heterogeneous graphs. Most studies on heterogeneous...
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A novel microbe-drug association prediction model based on graph attention networks and bilayer random forest
BackgroundIn recent years, the extensive use of drugs and antibiotics has led to increasing microbial resistance. Therefore, it becomes crucial to...
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Deterministic random walk model in NetLogo and the identification of asymmetric saturation time in random graph
Interactive programming environments are powerful tools for promoting innovative network thinking, teaching science of complexity, and exploring...
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Random Graph
The study of random graphs should go back to Erdős and Rényi (1947, 1959, 1960, 1961), in which they discovered that the random graphs were often...
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Efficient Knowledge Graph Embeddings via Kernelized Random Projections
Knowledge Graph Completion (KGC) aims to predict missing entities or relations in knowledge graph but it becomes computationally expensive as KG...
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A Note on the Distribution of the Extreme Degrees of a Random Graph via the Stein-Chen Method
We offer an alternative proof, using the Stein-Chen method, of Bollobás’ theorem concerning the distribution of the extreme degrees of a random...
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A Random Graph Model for Clustering Graphs
We introduce a random graph model for clustering graphs with a given degree sequence. Unlike previous random graph models, we incorporate clustering...