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Found 2 papers, 1 papers with code
Learning Topology-Specific Experts for Molecular Property Prediction
In this paper, motivated by this observation, we propose TopExpert to leverage topology-specific prediction models (referred to as experts), each of which is responsible for each molecular group sharing similar topological semantics.
Learnable Structural Semantic Readout for Graph Classification
By the help of a global readout operation that simply aggregates all node (or node-cluster) representations, existing GNN classifiers obtain a graph-level representation of an input graph and predict its class label using the representation.
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