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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/lirt1231/degreembed

공식 코드

DegreEmbed: incorporating entity embedding into logic rule learning for knowledge graph reasoning

https://github.com/lirt1231/kermit

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KERMIT: Knowledge Graph Completion of Enhanced Relation Modeling with Inverse Transformation

https://github.com/liu-jingzhe/graph-scaling-laws

공식 코드

Towards Neural Scaling Laws on Graphs

https://github.com/liu-yushan/PoLo

공식 코드

Neural Multi-Hop Reasoning With Logical Rules on Biomedical Knowledge Graphs

https://github.com/liu-yushan/calgnn

공식 코드

On Calibration of Graph Neural Networks for Node Classification

https://github.com/liu-yushan/tlogic

공식 코드

TLogic: Temporal Logical Rules for Explainable Link Forecasting on Temporal Knowledge Graphs

https://github.com/liuyuaa/GETD

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Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases

https://github.com/ljxw88/deephgcn

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DeepHGCN: Toward Deeper Hyperbolic Graph Convolutional Networks

https://github.com/llqy123/dabr

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Distance-Adaptive Quaternion Knowledge Graph Embedding with Bidirectional Rotation

https://github.com/lspongebobjh/virgo_icml2023

공식 코드

On the Initialization of Graph Neural Networks

https://github.com/luffycodes/neptune

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NePTuNe: Neural Powered Tucker Network for Knowledge Graph Completion

https://github.com/luka-group/prix-lm

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Prix-LM: Pretraining for Multilingual Knowledge Base Construction

https://github.com/luyi256/craft

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Future Link Prediction Without Memory or Aggregation

https://github.com/lxd99/tpnet

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Improving Temporal Link Prediction via Temporal Walk Matrix Projection

https://github.com/lza12a/unihr

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UniHR: Hierarchical Representation Learning for Unified Knowledge Graph Link Prediction

https://github.com/m-hildebrandt/R2D2

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Reasoning on Knowledge Graphs with Debate Dynamics

https://github.com/ma-compbio/Hyper-SAGNN

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Hyper-SAGNN: a self-attention based graph neural network for hypergraphs

https://github.com/magical-seven/mhsbm

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Community and hyperedge inference in multiple hypergraphs

https://github.com/mahesh-ak/cogdetect

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Automated Cognate Detection as a Supervised Link Prediction Task with Cognate Transformer

https://github.com/mahsa91/py_mgcn

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MGCN: Semi-supervised Classification in Multi-layer Graphs with Graph Convolutional Networks

https://github.com/mail-ecnu/otdyadicfair

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Obtaining Dyadic Fairness by Optimal Transport

https://github.com/mali-git/hyper_relational_ilp

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Improving Inductive Link Prediction Using Hyper-Relational Facts

https://github.com/malllabiisc/ASAP

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ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

https://github.com/malllabiisc/CompGCN

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Composition-based Multi-Relational Graph Convolutional Networks

https://github.com/malllabiisc/ConfGCN

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Neural Graph Embedding Methods for Natural Language Processing

https://github.com/malllabiisc/InteractE

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InteractE: Improving Convolution-based Knowledge Graph Embeddings by Increasing Feature Interactions

https://github.com/mandt-lab/knowledge-graph-tuning

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Augmenting and Tuning Knowledge Graph Embeddings

https://github.com/manhtuando97/two-stage-gnn

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Two-stage Training of Graph Neural Networks for Graph Classification

https://github.com/manoskary/musgconv

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Perception-Inspired Graph Convolution for Music Understanding Tasks

https://github.com/manoskary/vocsep_ijcai2023

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Musical Voice Separation as Link Prediction: Modeling a Musical Perception Task as a Multi-Trajectory Tracking Problem

https://github.com/marblet/GCNmf

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Graph Convolutional Networks for Graphs Containing Missing Features

https://github.com/marcob46/mpxgat

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MPXGAT: An Attention based Deep Learning Model for Multiplex Graphs Embedding

https://github.com/marina-sp/reinform

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ReInform: Selecting paths with reinforcement learning for contextualized link prediction

https://github.com/mariokrenn6240/futureofaiviaai

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Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network

https://github.com/mariotheone/gretel

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A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges

https://github.com/marlin-codes/HTGN

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Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning in Hyperbolic Space

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.