A quotient space formulation for generative statistical analysis of graphical data

DOI10.1007/s10851-021-01027-1OpenAlexW3141303149MaRDI QIDQ2036213

Anuj Srivastava, Sudeep Sarkar, Xiaoyang Guo

Publication date: 28 June 2021

Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1909.12907

zbMATH Keywords

graph matchinggraph statisticsgraph PCAmodeling graph variability

Mathematics Subject Classification ID

Computer science (68-XX) Information and communication theory, circuits (94-XX)

Related Items (2)

Statistical shape analysis of brain arterial networks (BAN) ⋮ Towards quotient barycentric subspaces

Uses Software

• GENeVis
• node2vec
• graph2vec
• DeepWalk
• LINE

Cites Work

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• Functional and shape data analysis
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• Averages of unlabeled networks: geometric characterization and asymptotic behavior
• Statistical graph space analysis
• Scaling algorithms for unbalanced optimal transport problems
• An eigendecomposition approach to weighted graph matching problems
• Discussion: Object-Oriented Data Analysis, Power Metrics, and Graph Laplacians
• Optimum Distribution of Switching Centers in a Communication Network and Some Related Graph Theoretic Problems
• Bridging the Gap between Graph Edit Distance and Kernel Machines

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