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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/text-machine-lab/transformerpy

Attention Is All You Need

https://github.com/tgebhart/sheaf_kg_transind

Inductive Logical Query Answering in Knowledge Graphs

https://github.com/thanhlong1997/bert_quora

Attention Is All You Need

https://github.com/the-Quert/iNLPfun

Attention Is All You Need

https://github.com/theQuert/inlpfun

Attention Is All You Need

https://github.com/thecodemasterk/BERT

Attention Is All You Need

https://github.com/thibaudmartinez/node2vec

node2vec: Scalable Feature Learning for Networks

https://github.com/thiviyant/intelligraphs

Embedding Entities and Relations for Learning and Inference in Knowledge Bases

https://github.com/thu-keg/eakit

Embedding Entities and Relations for Learning and Inference in Knowledge Bases

https://github.com/thumt/THUMT

Attention Is All You Need

https://github.com/thunlp-mt/ckd

Attention Is All You Need

https://github.com/tjcdev/gcmc-tf2

Graph Convolutional Matrix Completion

https://github.com/tjrwlgns1198/ChatBot

Attention Is All You Need

https://github.com/tlmakinen/GAT-noise

Graph Attention Networks

https://github.com/tobiasweede/rs-via-gnn

Graph Convolutional Matrix Completion

https://github.com/tomdyer10/fake_news

Attention Is All You Need

https://github.com/tonyPo/AMLSim_prep

EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

https://github.com/toooooodo/rgcn-linkprediction

Modeling Relational Data with Graph Convolutional Networks

https://github.com/tranhungnghiep/AnalyzingKGEmbeddings

MEIM: Multi-partition Embedding Interaction Beyond Block Term Format for Efficient and Expressive Link Prediction

https://github.com/tree-park/kor-to-eng-translation

Attention Is All You Need

https://github.com/tree-park/transformer_lm

Attention Is All You Need

https://github.com/truclycs/ocr_seq2seq

Attention Is All You Need

https://github.com/tshu-w/dbcopilot

Attention Is All You Need

https://github.com/tshu-w/llm4em

Attention Is All You Need

https://github.com/tsy935/readmit-stgnn

GNNExplainer: Generating Explanations for Graph Neural Networks

https://github.com/tubamuzzaffar/g

Graph Convolutional Matrix Completion

https://github.com/tubamuzzaffar/gc

Graph Convolutional Matrix Completion

https://github.com/tubamuzzaffar/gc2

Graph Convolutional Matrix Completion

https://github.com/tubamuzzaffar/gcmc-2

Graph Convolutional Matrix Completion

https://github.com/tvinith/bert

Attention Is All You Need

https://github.com/twjiang/graphSAGE-pytorch

Inductive Representation Learning on Large Graphs

https://github.com/twktheainur/kbc

Canonical Tensor Decomposition for Knowledge Base Completion

https://github.com/tyxr/bert

Attention Is All You Need

https://github.com/tyxxzjpdez/GCNII-DropGroups

Simple and Deep Graph Convolutional Networks

https://github.com/u7javed/Transformer-Multi-Language-Translator

Attention Is All You Need

https://github.com/uclmr/inferbeddings

Adversarial Sets for Regularising Neural Link Predictors

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