Abstract: In the era of information explosion, clustering analysis of graph-structured data and empty graph-structured data is of great significance for extracting the intrinsic value of data. From ...
Abstract: The non-Euclidean nature of graphs made them inaccessible to standard deep learning techniques that rely on fixed-size, ordered inputs. Graph Neural Networks (GNNs) are essential for serving ...
This repository contains the official implementation of the paper "Boosting Graph Neural Networks via Adaptive Knowledge Distillation". This work proposes a novel knowledge distillation framework for ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback