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Found 2 papers, 2 papers with code
Disentangling Node Attributes from Graph Topology for Improved Generalizability in Link Prediction
Our proposed method, UPNA (Unsupervised Pre-training of Node Attributes), solves the inductive link prediction problem by learning a function that takes a pair of node attributes and predicts the probability of an edge, as opposed to Graph Neural Networks (GNN), which can be prone to topological shortcuts in graphs with power-law degree distribution.
AI-Bind: Improving Binding Predictions for Novel Protein Targets and Ligands
Identifying novel drug-target interactions (DTI) is a critical and rate limiting step in drug discovery.
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