Results 11 to 20 of about 22,057,993 (342)
The Gaussian Graphical Model in Cross-Sectional and Time-Series Data [PDF]
Multivariate Behavioral Research, 2016 We discuss the Gaussian graphical model (GGM; an undirected network of partial correlation coefficients) and detail its utility as an exploratory data analysis tool.
S. Epskamp +3 more
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Community Detection in Social Networks Considering Social Behaviors
IEEE Access, 2022 The study of community detection in networks has drawn great attention in recent years. To find communities and to understand community semantics, both network topology and network content are utilized. Unfortunately, none of them can explain the driving
Yingkui Wang +4 more
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Undirected Structural Markov Property for Bayesian Model Determination
Mathematics, 2023 This paper generalizes the structural Markov properties for undirected decomposable graphs to arbitrary ones. This helps us to exploit the conditional independence properties of joint prior laws to analyze and compare multiple graphical structures, while
Xiong Kang, Yingying Hu, Yi Sun
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Functional Graphical Models [PDF]
Journal of the American Statistical Association, 2018 Graphical models have attracted increasing attention in recent years, especially in settings involving high-dimensional data. In particular, Gaussian graphical models are used to model the conditional dependence structure among multiple Gaussian random variables.
Qiao, Xinghao +2 more
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Partition-Merge: Distributed Inference and Modularity Optimization
IEEE Access, 2021 This paper presents a novel meta-algorithm, Partition-Merge (PM), which takes existing centralized algorithms for graph computation and makes them distributed and faster. In a nutshell, PM divides the graph into small subgraphs using our novel randomized
Vincent Blondel +4 more
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Elliptical graphical modelling [PDF]
Biometrika, 2011 We propose elliptical graphical models based on conditional uncorrelatedness as a general- ization of Gaussian graphical models by letting the population distribution be elliptical instead of normal, allowing the fitting of data with arbitrarily heavy tails.
D. Vogel, R. Fried
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Graphical Models for Extremes [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2020 SummaryConditional independence, graphical models and sparsity are key notions for parsimonious statistical models and for understanding the structural relationships in the data. The theory of multivariate and spatial extremes describes the risk of rare events through asymptotically justified limit models such as max-stable and multivariate Pareto ...
Sebastian Engelke, Adrien S. Hitz
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Interpretation of 3-D scene through LiDAR point clouds has been a hot research topic for decades. To utilize measured points in the scene, assigning unique tags to the points of the scene with labels linking to individual objects plays a crucial role in ...
Yusheng Xu +6 more
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Detecting Community Evolution by Utilizing Individual Temporal Semantics in Social Networks
IEEE Access, 2023 Social networks are becoming increasingly popular and significant. One of the most distinctive features of these networks is their dynamic nature, which means that they change over time.
Feng Wang, Dingbo Hou, Hao Yan
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When is a Network a Network?: Multi-Order Graphical Model Selection in Pathways and Temporal Networks [PDF]
Knowledge Discovery and Data Mining, 2017 We introduce a framework for the modeling of sequential data capturing pathways of varying lengths observed in a network. Such data are important, e.g., when studying click streams in the Web, travel patterns in transportation systems, information ...
Ingo Scholtes
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