Inductive Relation Prediction

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11 shown of 11 papers with code (14 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Inductive Relation Prediction by Subgraph Reasoning
  16 Nov 2019 10 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  The dominant paradigm for relation prediction in knowledge graphs involves learning and operating on latent representations (i.
• Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction
  13 Jun 2021 3 repositories listed Syntology ran 2 of 15 samples · 13 unverified
  To further improve the capacity of the path formulation, we propose the Neural Bellman-Ford Network (NBFNet), a general graph neural network framework that solves the path formulation with learned operators in the…
• Learning Rule-Induced Subgraph Representations for Inductive Relation Prediction
  9 Aug 2024 1 repository listed
  Specifically, we propose a \textit{single-source} initialization approach to initialize edge features only for the target link, which guarantees the relevance of mined rules and target link.
• Anchoring Path for Inductive Relation Prediction in Knowledge Graphs
  21 Dec 2023 1 repository listed
  To address this challenge, we propose Anchoring Path Sentence Transformer (APST) by introducing Anchoring Paths (APs) to alleviate the reliance of CPs.
• Extending Transductive Knowledge Graph Embedding Models for Inductive Logical Relational Inference
  7 Sep 2023 1 repository listed
  In this work, we bridge the gap between traditional transductive knowledge graph embedding approaches and more recent inductive relation prediction models by introducing a generalized form of harmonic extension which…
• Inductive Relation Prediction from Relational Paths and Context with Hierarchical Transformers
  1 Apr 2023 1 repository listed
  Relation prediction on knowledge graphs (KGs) is a key research topic.
• Multi-Aspect Explainable Inductive Relation Prediction by Sentence Transformer
  4 Jan 2023 1 repository listed
  Recent studies on knowledge graphs (KGs) show that path-based methods empowered by pre-trained language models perform well in the provision of inductive and explainable relation predictions.
• Meta-Knowledge Transfer for Inductive Knowledge Graph Embedding
  27 Oct 2021 1 repository listed
  In this paper, to achieve inductive knowledge graph embedding, we propose a model MorsE, which does not learn embeddings for entities but learns transferable meta-knowledge that can be used to produce entity embeddings.
• Cycle Representation Learning for Inductive Relation Prediction
  6 Oct 2021 1 repository listed
  In this paper, we consider rules as cycles and show that the space of cycles has a unique structure based on the mathematics of algebraic topology.
• Inductive Relation Prediction by BERT
  12 Mar 2021 1 repository listed
  Relation prediction in knowledge graphs is dominated by embedding based methods which mainly focus on the transductive setting.
• Communicative Message Passing for Inductive Relation Reasoning
  16 Dec 2020 1 repository listed
  Relation prediction for knowledge graphs aims at predicting missing relationships between entities.

Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.