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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/nameoverflow/neuro-cangjie

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https://github.com/natel9178/transformer-refork

Attention Is All You Need

https://github.com/nathann3/better_than_netflix_movie_recommender

Neural Graph Collaborative Filtering

https://github.com/nealgravindra/self-supervsed_edge_feats

Self-supervised edge features for improved Graph Neural Network training

https://github.com/neburseni/NLP

Attention Is All You Need

https://github.com/neqkir/attention-mechanism

Attention Is All You Need

https://github.com/ngocphucck/BERT-questions-classification

Attention Is All You Need

https://github.com/niccolot/ENG-ITA_NMT

Attention Is All You Need

https://github.com/nicholasbao/nlp_job

Attention Is All You Need

https://github.com/nietao2/DeepSpeechRecognition

Attention Is All You Need

https://github.com/ninghaohello/Polysemous-Network-Embedding

Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding

https://github.com/ninoxjy/graph-embedding

LINE: Large-scale Information Network Embedding

https://github.com/nishnik/poincare_embeddings

Poincaré Embeddings for Learning Hierarchical Representations

https://github.com/njuhtc/LEDG

EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

https://github.com/nlinc1905/dsilt-tsa

Attention Is All You Need

https://github.com/nmfisher/bert-modified

Attention Is All You Need

https://github.com/nmvdlei/PPMI_MAGNN

MAGNN: Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding

https://github.com/nnaakkaaii/g2-MLP

Graph Attention Networks

https://github.com/noahtren/Graph-Attention-Networks-TensorFlow-2

Graph Attention Networks

https://github.com/noamrazin/gnn_interactions

A Unified Lottery Ticket Hypothesis for Graph Neural Networks

https://github.com/nonofefe/GCN_mean

Graph Convolutional Networks for Graphs Containing Missing Features

https://github.com/noriyukipy/tfchat

Attention Is All You Need

https://github.com/noriyukipy/tfdlg

Attention Is All You Need

https://github.com/nrc-cnrc/sockeye-multisource

Attention Is All You Need

https://github.com/nsfzyzz/generalization_metrics_for_nlp

Attention Is All You Need

https://github.com/nslab-cuk/community-aware-graph-transformer

Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-based Similarity

https://github.com/ntkien1904/LHGNN

Link Prediction on Latent Heterogeneous Graphs

https://github.com/nvshrao/Bidirectional-Transformer

Attention Is All You Need

https://github.com/okkteam/Transformer-Transducer

Attention Is All You Need

https://github.com/olety/TIMLinUCB

node2vec: Scalable Feature Learning for Networks

https://github.com/ololo123321/maestro

Attention Is All You Need

https://github.com/open-mmlab/mmclassification

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https://github.com/opennmt/ctranslate2

Attention Is All You Need

https://github.com/otiliastr/coper

https://github.com/owainwest/uniprot_bert

Attention Is All You Need

https://github.com/paolanu/BERT_epitope

Attention Is All You Need

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