Combining graph wavelet embeddings with Neural Bellman-Ford message passing reduces the layers needed for inductive logical query answering on large knowledge graphs.
Observed versus latent features for knowl- edge base and text inference
3 Pith papers cite this work. Polarity classification is still indexing.
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Introduces the relation set completion task and RelSetE embedding model to infer missing entity-compatible relations by modeling latent patterns in observed relations, evaluated on three derived KG benchmarks.
CORE embeds relations as cyclic orthotopes on a torus with adaptive width regularization to enable boundary-less optimization and capture complex logical patterns in knowledge graphs.
citing papers explorer
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InductWave: Inductive Multi-Hop Logical Query Answering on Knowledge Graphs
Combining graph wavelet embeddings with Neural Bellman-Ford message passing reduces the layers needed for inductive logical query answering on large knowledge graphs.
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Beyond Triplet Plausibility: Relation Set Completion in Knowledge Graphs
Introduces the relation set completion task and RelSetE embedding model to infer missing entity-compatible relations by modeling latent patterns in observed relations, evaluated on three derived KG benchmarks.
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CORE: Cyclic Orthotope Relation Embedding for Knowledge Graph Completion
CORE embeds relations as cyclic orthotopes on a torus with adaptive width regularization to enable boundary-less optimization and capture complex logical patterns in knowledge graphs.