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Graph Classification Gaussian Processes via Spectral Features
Graph classification aims to categorise graphs based on their structure and node attributes.
Transductive Kernels for Gaussian Processes on Graphs
To address this, we present a novel, generalized kernel for graphs with node feature data for semi-supervised learning.
Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets
Graph-based models require aggregating information in the graph from neighbourhoods of different sizes.
Gaussian Processes on Graphs via Spectral Kernel Learning
We propose a graph spectrum-based Gaussian process for prediction of signals defined on nodes of the graph.
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