Embedding graphs on Grassmann manifold

DOI10.1016/J.NEUNET.2022.05.001MaRDI QIDQ6488709

Bingxin Zhou, Xuebin Zheng, Ming Li, Yu Guang Wang, Junbin Gao

Publication date: 17 October 2023

Published in: Neural Networks (Search for Journal in Brave)

zbMATH Keywords

Grassmann manifoldsubspace clusteringgraph neural networkprojection embedding

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

• Unnamed Item
• Algorithmic advances in Riemannian geometry and applications. For machine learning, computer vision, statistics, and optimization
• Gromov-Wasserstein distances and the metric approach to object matching
• Riemannian geometry of Grassmann manifolds with a view on algorithmic computation
• Statistics on special manifolds
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• Schubert Varieties and Distances between Subspaces of Different Dimensions
• The Geometry of Algorithms with Orthogonality Constraints
• Clustering on Multi-Layer Graphs via Subspace Analysis on Grassmann Manifolds
• Least squares quantization in PCM
• Manifold Optimization-Assisted Gaussian Variational Approximation
• Graph Representation Learning
• Expanding the Family of Grassmannian Kernels: An Embedding Perspective
• A Geometric Approach to Low-Rank Matrix Completion
• Dynamical Low‐Rank Approximation

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