Papers with Code 아카이브
Link Prediction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
- 79
- 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.
https://github.com/ArvidWartenberg/retrosynthesis
https://github.com/Arvidsmile/InductiveDialogueGraph
https://github.com/AssafSinger94/sigmorphon-2020-inflection
https://github.com/AtluriNikhil/Image-Captioning
https://github.com/AutoML-4Paradigm/ERAS
NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding
https://github.com/AutoML-4Paradigm/NSCaching
NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding
https://github.com/AutoML-4Paradigm/S2S
NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding
https://github.com/AutoML-Research/KGBench
NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs
https://github.com/AutoML-Research/S2S
NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding
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https://github.com/Aveek-Saha/Transformer
https://github.com/BIG-S2/keras-gnm
https://github.com/BasileBron/Artificial-Intelligence-Lexical
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https://github.com/BrianPulfer/PapersReimplementations
https://github.com/CGCL-codes/naturalcc
https://github.com/CHFsky/GCC-paddle
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training
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https://github.com/CVxTz/music_genre_classification
https://github.com/Caesarzhang/bert-zh
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https://github.com/Charliesgithub20221030/BERT
https://github.com/ChengSashankh/trying-GAT
https://github.com/ChengyuSun/gat
https://github.com/Chenxingyu1990/A-Boundary-Based-Out-of-Distribution-Classifier-for-Generalized-Zero-Shot-Learning
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https://github.com/Chinnu1103/Machine-Translation-using-Transformers
https://github.com/Chonwai/Learning_BERT
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https://github.com/DM2-ND/CoEvoGNN
Learning Attribute-Structure Co-Evolutions in Dynamic Graphs
https://github.com/DaehanKim/vgae_pytorch
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.