Papers with Code 아카이브
Link Prediction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
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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.
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A Probabilistic Framework for Knowledge Graph Data Augmentation
https://github.com/anonymous-dense-submission/DensE
https://github.com/anshul3899/GNNExplainer-Experiments
GNNExplainer: Generating Explanations for Graph Neural Networks
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EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
https://github.com/ant-research/KnowledgeGraphEmbeddingsViaPairedRelationVectors_PairRE
PairRE: Knowledge Graph Embeddings via Paired Relation Vectors
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https://github.com/anton-bushuiev/ppiformer
https://github.com/anuscode/nrms
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Tensor Decompositions for temporal knowledge base completion
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Neural Collaborative Filtering vs. Matrix Factorization Revisited
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NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding
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Embedding Entities and Relations for Learning and Inference in Knowledge Bases
https://github.com/awslabs/sockeye
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https://github.com/bachnguyente/temporal-mgn
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https://github.com/baotramduong/Sentiment-Analysis-with-Deep-Learning-using-BERT
https://github.com/baotramduong/Twitter-Sentiment-Analysis-with-Deep-Learning-using-BERT
https://github.com/bartzi/chainer-transformer
https://github.com/basile-bron/Artificial-Intelligence-Lexical
https://github.com/basiralab/HADA
Adversarially Regularized Graph Autoencoder for Graph Embedding
https://github.com/basiralab/HCAE
Adversarially Regularized Graph Autoencoder for Graph Embedding
https://github.com/basiralab/LG-DADA
Adversarially Regularized Graph Autoencoder for Graph Embedding
https://github.com/basiralab/RG-Select
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.