Link Prediction

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Benchmarks

Citeseer (nonstandard variant)

결과 1개

Most implemented

Modeling Relational Data with Graph Convolutional Networks

2017-03-17 · 구현 27개

Variational Graph Auto-Encoders

2016-11-21 · 구현 22개

Neural Graph Collaborative Filtering

2019-05-20 · 구현 21개

Inductive Representation Learning on Large Graphs

2017-06-07 · 구현 20개

Papers

PyKEEN-NSX: A Modular Framework for Static, Dynamic and Schema-Aware Negative Sampling in PyKEEN

2026-08-31 · Ivan Diliso, Nicola Fanizzi, Claudia d'Amato arxiv

Embedding methods have become popular due to their scalability on link prediction and/or triple classification tasks on Knowledge Graphs (KGs). Embedding models are trained relying on both positive and negative samples o…

Knowledge Graph Embedding Triple Classification Knowledge Graphs Link Prediction

Neural Regression with Embeddings for Numerical Attribute Prediction in Knowledge Graphs

2026-08-27 · Rupesh Sapkota, Louis Mozart Kamdem Teyou, Moshood Yekini, Caglar Demir 외 arxiv

In recent years, transductive knowledge graph embedding models have been applied to tasks such as link prediction and query answering. Although knowledge graphs often contain rich numerical attributes, most embedding mod…

Knowledge Graph Embedding Knowledge Graphs Link Prediction

Hierarchy-Aware Semantic Losses for Knowledge Graph Link Prediction

2026-08-24 · Filip Kronström, Ross D. King arxiv

Knowledge graphs are often accompanied by ontological class hierarchies that encode valuable semantic information, yet many link prediction methods either ignore such hierarchies or incorporate them indirectly through ad…

Representation Learning Graph Neural Network Knowledge Graphs Link Prediction

ReCoG: Reciprocal Co-Evolution for Multimodal Graph Learning

2026-08-24 · Rui Xue, Tianfu Wu arxiv

Multimodal graph learning requires jointly training over graph structure and heterogeneous node attributes, yet existing methods largely decouple these processes: prior multimodal graph neural networks (GNNs) focus on al…

Graph structure learning Representation Learning Node Classification Link Prediction

Fairness-Aware Network Embeddings: Methods, Applications, and Challenges

2026-08-19 · Ella Has, Harshith Kumar Yadav, Gaurav Dixit, Mykola Pechenizkiy 외 arxiv

Network embedding methods learn low-dimensional representations of graph-structured data to support downstream tasks such as node classification, link prediction, and influence maximization. However, real-world networks …

Representation Learning Graph Neural Network Node Classification Link Prediction

Dynamic Graph Prompting via Topology-Routed Mixed-Curvature Experts

2026-08-06 · Quanxin Wang, Xuanting Xie, Bingheng Li, Xingtong Yu 외 arxiv

Dynamic graph prompting freezes a pre-trained temporal backbone and adapts it to label-scarce downstream tasks using lightweight prompts. However, existing methods operate within a single, fixed embedding space. In this …

Node Classification Link Prediction

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