Abstract: Graph Knowledge Distillation (GKD) has made remarkable progress in graph representation learning in recent years. Despite its great success, GKD often obeys the label-dependence manner, ...
Abstract: Stock trend prediction involves forecasting the future price movements by analyzing historical data and various market indicators. With the advancement of machine learning, graph neural ...
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 ...
To address the trade-off between noisy full-graph modeling and information loss in simplified graphs, we propose a Progressive Multi-View Graph Distillation paradigm (PMVGD) for health event ...
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