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Found 4 papers, 3 papers with code
Improving Subgraph-GNNs via Edge-Level Ego-Network Encodings
We present a novel edge-level ego-network encoding for learning on graphs that can boost Message Passing Graph Neural Networks (MP-GNNs) by providing additional node and edge features or extending message-passing formats.
Beyond 1-WL with Local Ego-Network Encodings
Identifying similar network structures is key to capture graph isomorphisms and learn representations that exploit structural information encoded in graph data.
Uncovering the Limits of Text-based Emotion Detection
Identifying emotions from text is crucial for a variety of real world tasks.
Inductive Graph Embeddings through Locality Encodings
Learning embeddings from large-scale networks is an open challenge.
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