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Abstract: Knowledge graph embedding (KGE) aims at learning powerful representations to benefit various artificial intelligence applications. Meanwhile, contrastive learning has been widely leveraged ...

Abstract: Attributed graph clustering aims to partition nodes of a graph structure into different groups. Recent works usually use variational graph autoencoder (VGAE) to make the node representations ...

This repository is the official implementation of KANO, which is model proposed in a paper: Knowledge graph-enhanced molecular contrastive learning with functional prompt. Firstly, we construct a ...

We uploaded the test datasets and models using git lfs. You must install it to clone the repo correctly. The default optional arguments are those used in the paper. A ...