Link Prediction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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.
https://github.com/VedantYadav/Transformer
https://github.com/VisiumCH/AMLD-2021-Graphs
GNNExplainer: Generating Explanations for Graph Neural Networks
https://github.com/VoVAllen/diffpool
Hierarchical Graph Representation Learning with Differentiable Pooling
https://github.com/Walter-B/bert-20-classes
https://github.com/WantingZhao/my_GAT
https://github.com/Wei9711/NegGCNs
Understanding Negative Sampling in Graph Representation Learning
https://github.com/WeidongLi-KG/KBGAN_PyTorch-v0.4.1
https://github.com/WenYanger/General-Transformer-Pytorch
https://github.com/WenjieDu/PyPOTS
https://github.com/WiktorJ/msnode2vec
https://github.com/Wolfie8935/Implementation-of-Attention-is-all-you-need
https://github.com/XINZXZHANG/Bert_repo
https://github.com/XUJitao/WordEmbedding
https://github.com/XapaJIaMnu/transformative
https://github.com/Xinsen-Zhang/transformer
https://github.com/XuhanLiu/Transformer
https://github.com/YYGXjpg/BERT_WL
https://github.com/Yindong-Zhang/myGAT
https://github.com/Yipeng91/text_classifier_pub
https://github.com/YuanEric88/bert-nlu
https://github.com/YunseobShin/wiki_GAT
https://github.com/Zehui127/SQUAD_BERT
https://github.com/ZerixU/CSNS
https://github.com/ZmeiGorynych/transformer_pytorch
https://github.com/ZurichNLP/sockeye
https://github.com/a414351664/Bert_MRC
https://github.com/aaronH45/sentimentAnalysis
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https://github.com/abhaskumarsinha/Keras-implementation-of-Transformer-Architecture
https://github.com/abhaskumarsinha/Keras-implementation-of-Transformer-Architecture/blob/main/Transformer.py
https://github.com/abhaskumarsinha/MinimalGPT
https://github.com/abhiagg92/bert_sentiment
https://github.com/abhilash1910/Deep-Graph-Learning
https://github.com/abhilash1910/GraphAttentionNetworks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.