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Found 4 papers, 1 papers with code
Knowledge Graph Embedding: A Survey from the Perspective of Representation Spaces
Particularly, we build a fine-grained classification to categorise the models based on three mathematical perspectives of the representation spaces: (1) Algebraic perspective, (2) Geometric perspective, and (3) Analytical perspective.
Structure-Aware Random Fourier Kernel for Graphs
Gaussian Processes (GPs) define distributions over functions and their generalization capabilities depend heavily on the choice of kernels.
Variational Continual Bayesian Meta-Learning
Conventional meta-learning considers a set of tasks from a stationary distribution.
Semi-supervisedly Co-embedding Attributed Networks
Deep generative models (DGMs) have achieved remarkable advances.
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