3 citations · 4 across the 4 of their papers we have counts for
4 papers · 1 filter
Graph Classification Gaussian Processes via Spectral Features
Felix L. Opolka, Yin-Cong Zhi, Pietro Liò +1
Graph classification aims to categorise graphs based on their structure and node attributes. In this work, we propose to tackle this task using tools from graph signal processing b…
Transductive Kernels for Gaussian Processes on Graphs
Yin-Cong Zhi, Felix L. Opolka, Yin Cheng Ng +2
Kernels on graphs have had limited options for node-level problems. To address this, we present a novel, generalized kernel for graphs with node feature data for semi-supervised le…
Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets
Felix L. Opolka, Yin-Cong Zhi, Pietro Liò +1
Graph-based models require aggregating information in the graph from neighbourhoods of different sizes. In particular, when the data exhibit varying levels of smoothness on the gra…
Gaussian Processes on Graphs via Spectral Kernel Learning
Yin-Cong Zhi, Yin Cheng Ng, Xiaowen Dong
We propose a graph spectrum-based Gaussian process for prediction of signals defined on nodes of the graph. The model is designed to capture various graph signal structures through…