research
∙
06/06/2023
Graph Classification Gaussian Processes via Spectral Features
Graph classification aims to categorise graphs based on their structure ...
share
research
∙
11/28/2022
Transductive Kernels for Gaussian Processes on Graphs
Kernels on graphs have had limited options for node-level problems. To a...
research
∙
10/25/2021
Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets
Graph-based models require aggregating information in the graph from nei...
research
∙
04/03/2021
Adaptive Filters and Aggregator Fusion for Efficient Graph Convolutions
Training and deploying graph neural networks (GNNs) remains difficult du...
research
∙
04/24/2020
Learning Mobility Flows from Urban Features with Spatial Interaction Models and Neural Networks
A fundamental problem of interest to policy makers, urban planners, and ...
research
∙
02/11/2020
Graph Convolutional Gaussian Processes For Link Prediction
Link prediction aims to reveal missing edges in a graph. We address this...
research
∙
04/12/2019