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Link Prediction

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하위 태스크: 6
평가표: 79
보존된 평가 기록: 497

Link Prediction is a task in graph and network analysis where the goal is to predict missing or future connections between nodes in a network. Given a partially observed network, the goal of link prediction is to infer which links are most likely to be added or missing based on the observed connections and the structure of the network.

<span style="color:grey; opacity: 0.6">( Image credit: Inductive Representation Learning on Large Graphs )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/abdouskamel/hmge

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Hierarchical Aggregations for High-Dimensional Multiplex Graph Embedding

https://github.com/aday651/embed-asym-exeriments

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Asymptotics of Network Embeddings Learned via Subsampling

https://github.com/aday651/embed-asym-experiments

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Asymptotics of Network Embeddings Learned via Subsampling

https://github.com/aday651/embed-reg

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Asymptotics of $\ell_2$ Regularized Network Embeddings

https://github.com/aditya-grover/node2vec

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node2vec: Scalable Feature Learning for Networks

https://github.com/ahmadihafez/ConvDySAT

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ConvDySAT: Deep Neural Representation Learning on Dynamic Graphs via Self-Attention and Convolutional Neural Networks

https://github.com/ahmadkhajehnejad/CrossWalk

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CrossWalk: Fairness-enhanced Node Representation Learning

https://github.com/ahmedesamy/leap

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Leap: Inductive Link Prediction via Learnable TopologyAugmentation

https://github.com/aida-ugent/DeBayes

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DeBayes: a Bayesian Method for Debiasing Network Embeddings

https://github.com/aida-ugent/MaxEntComb

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Block-Approximated Exponential Random Graphs

https://github.com/aida-ugent/NRL4LP

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Benchmarking Network Embedding Models for Link Prediction: Are We Making Progress?

https://github.com/aida-ugent/dlp_exploration

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Exploring the Performance of Continuous-Time Dynamic Link Prediction Algorithms

https://github.com/aida-ugent/dlp_viz

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New Perspectives on the Evaluation of Link Prediction Algorithms for Dynamic Graphs

https://github.com/aistairc/RDF-star2Vec

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RDF-star2Vec: RDF-star Graph Embeddings for Data Mining

https://github.com/aistairc/kgrc-rdf-star

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RDF-star2Vec: RDF-star Graph Embeddings for Data Mining

https://github.com/ajabri/videowalk

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Space-Time Correspondence as a Contrastive Random Walk

https://github.com/akanshaaga/reg_appnp

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Addressing the Impact of Localized Training Data in Graph Neural Networks

https://github.com/akastrin/ida2025lbd

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Make Literature-Based Discovery Great Again through Reproducible Pipelines

https://github.com/akula01/DeepFork

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DeepFork: Supervised Prediction of Information Diffusion in GitHub

https://github.com/alanjohnvarghese/TransformerG2G

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TransformerG2G: Adaptive time-stepping for learning temporal graph embeddings using transformers

https://github.com/alexanderimanicowenrivers/Neural-Variational-Knowledge-Graphs

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Neural Variational Inference For Estimating Uncertainty in Knowledge Graph Embeddings

https://github.com/alge24/DyGNN

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Streaming Graph Neural Networks

https://github.com/alipay/KnowledgeGraphEmbeddingsViaPairedRelationVectors_PairRE

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PairRE: Knowledge Graph Embeddings via Paired Relation Vectors

https://github.com/alipay/parameter_inference_efficient_pie

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PIE: a Parameter and Inference Efficient Solution for Large Scale Knowledge Graph Embedding Reasoning

https://github.com/amaiya/ktrain

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ktrain: A Low-Code Library for Augmented Machine Learning

https://github.com/amal-gader/genic

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GenIC: An LLM-Based Framework for Instance Completion in Knowledge Graphs

https://github.com/amazon-research/tgl

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TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs

https://github.com/amazon-science/convolution-matching

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Graph Coarsening via Convolution Matching for Scalable Graph Neural Network Training

https://github.com/amazon-science/dual-channel-hypergraph-neural-network

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Search Behavior Prediction: A Hypergraph Perspective

https://github.com/amazon-science/gnn-tail-generalization

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You Only Transfer What You Share: Intersection-Induced Graph Transfer Learning for Link Prediction

https://github.com/amazon-science/network-usable-info-framework

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NetInfoF Framework: Measuring and Exploiting Network Usable Information

https://github.com/amazon-science/page-link-path-based-gnn-explanation

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PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction

https://github.com/ameyagodbole/Prob-CBR

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Probabilistic Case-based Reasoning for Open-World Knowledge Graph Completion

https://github.com/aminfadaee/culp

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Classification Using Link Prediction

https://github.com/amrhssn/teneNCE

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Contrastive Representation Learning for Dynamic Link Prediction in Temporal Networks

https://github.com/amzn/pecos

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Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction

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