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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/uclmr/ntp

End-to-End Differentiable Proving

https://github.com/uclnlp/jack

Jack the Reader - A Machine Reading Framework

https://github.com/uma-pi1/dist-kge

Start Small, Think Big: On Hyperparameter Optimization for Large-Scale Knowledge Graph Embeddings

https://github.com/uma-pi1/kge-iclr20

Convolutional 2D Knowledge Graph Embeddings

https://github.com/umeiko/mindspore-seq2seq

Attention Is All You Need

https://github.com/urielsinger/ctdne

node2vec: Scalable Feature Learning for Networks

https://github.com/urielsinger/fairwalk

node2vec: Scalable Feature Learning for Networks

https://github.com/usherwang02/SemanticMatchingEnergy-Theano

Combining Two And Three-Way Embeddings Models for Link Prediction in Knowledge Bases

https://github.com/uzi0espil/research-papers-implementation/tree/master/Attention%20Is%20All%20You%20Need

Attention Is All You Need

https://github.com/vailatuts/SSFG-regularization

Graph Attention Networks

https://github.com/valentinmace/noisy-text

Attention Is All You Need

https://github.com/vanpersie32/Multigpu-Bert

Attention Is All You Need

https://github.com/vanslerry/long_text

Attention Is All You Need

https://github.com/veekaybee/what_are_embeddings

Attention Is All You Need

https://github.com/venomouscyanide/S3GRL_OGB

Link Prediction Based on Graph Neural Networks

https://github.com/vermouthdky/SimTeG

SimTeG: A Frustratingly Simple Approach Improves Textual Graph Learning

https://github.com/vfcarida/Can-NetGAN-be-improved-on-short-random-walks-

Can NetGAN be improved on short random walks?

https://github.com/vijay120/bert

Attention Is All You Need

https://github.com/vikashranjan/transformer

Attention Is All You Need

https://github.com/vinairesearch/phogpt

Attention Is All You Need

https://github.com/vinayprabhu/X-is-all-you-need

Attention Is All You Need

https://github.com/vishnuanil122/Bert-Binary-Text-Classifier

Attention Is All You Need

https://github.com/vpj/jax_transformer

Attention Is All You Need

https://github.com/vulus98/rethinking-attention

Attention Is All You Need

https://github.com/vvvm23/TchAIkovsky-Legacy

Attention Is All You Need

https://github.com/walkacross/transformer-pytorch

Attention Is All You Need

https://github.com/wan2000/mc-mot

Graph Attention Networks

https://github.com/wangmz15/Chinese-Error-Correction-with-THUMT

Attention Is All You Need

https://github.com/wayalhruhi/gogle_bert

Attention Is All You Need

https://github.com/wchh127/yykf

Attention Is All You Need

https://github.com/wei9711/d2gcn

Understanding Negative Sampling in Graph Representation Learning

https://github.com/weiyangfb/PyTorchSparseGAT

Graph Attention Networks

https://github.com/weiyinwei/huign

Inductive Representation Learning on Large Graphs

https://github.com/weiyinwei/mmgcn

Inductive Representation Learning on Large Graphs

https://github.com/whr94621/NJUNMT-pytorch

Attention Is All You Need

https://github.com/whut2962575697/gat_sementic_segmentation

Graph Attention Networks

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