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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/bishengli0327/bsal

공식 코드

BSAL: A Framework of Bi-component Structure and Attribute Learning for Link Prediction

https://github.com/bluer555/KernelGCN

공식 코드

Rethinking Kernel Methods for Node Representation Learning on Graphs

https://github.com/bojarlab/gifflar

공식 코드

Higher-Order Message Passing for Glycan Representation Learning

https://github.com/borgwardtlab/neuralwalker

공식 코드

Learning Long Range Dependencies on Graphs via Random Walks

https://github.com/boxorange/QC-LinkPrediction

공식 코드

Enhancing Future Link Prediction in Quantum Computing Semantic Networks through LLM-Initiated Node Features

https://github.com/brs96/geometric-instability-gnn-large-graphs

공식 코드

Geometric instability of graph neural networks on large graphs

https://github.com/buffoni/quantum-link-prediction

공식 코드

Network-based link prediction of scientific concepts -- a Science4Cast competition entry

https://github.com/bwilder0/clusternet

공식 코드

End to end learning and optimization on graphs

https://github.com/bwittmann/gav

공식 코드

Link Prediction for Flow-Driven Spatial Networks

https://github.com/bxshi/ConMask

공식 코드

Open-World Knowledge Graph Completion

https://github.com/cai-lw/KBGAN

공식 코드

KBGAN: Adversarial Learning for Knowledge Graph Embeddings

https://github.com/canlinzhang/siailp

공식 코드

Inductive Link Prediction in Knowledge Graphs using Path-based Neural Networks

https://github.com/caojiangxia/BiGI

공식 코드

Bipartite Graph Embedding via Mutual Information Maximization

https://github.com/carpenter-singh-lab/motive

공식 코드

MOTIVE: A Drug-Target Interaction Graph For Inductive Link Prediction

https://github.com/catarina-canastra/benchmarking-knowledge-graph-embeddings-for-gene-disease-association-prediction

공식 코드

A Systematic Evaluation of Knowledge Graph Embeddings for Gene-Disease Association Prediction

https://github.com/causalkg/causallp

공식 코드

CausalLP: Learning causal relations with weighted knowledge graph link prediction

https://github.com/cborile/eval_lp_xai

공식 코드

Evaluating Link Prediction Explanations for Graph Neural Networks

https://github.com/cchao0116/CTSMA-ICML21

공식 코드

Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation

https://github.com/cchao0116/EasyDGL

공식 코드

EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph Learning

https://github.com/cenyk1230/GATNE

공식 코드

Representation Learning for Attributed Multiplex Heterogeneous Network

https://github.com/cf020031308/mad-learning

공식 코드

Memory-Associated Differential Learning

https://github.com/charles-pyj/bridging-ai-and-science

공식 코드

Bridging AI and Science: Implications from a Large-Scale Literature Analysis of AI4Science

https://github.com/charusharma1991/LinkPred

공식 코드

Learning Representations using Spectral-Biased Random Walks on Graphs

https://github.com/chenjie20/cgcl

공식 코드

Cross-View Graph Consistency Learning for Invariant Graph Representations

https://github.com/chennnM/GCNII

공식 코드

Simple and Deep Graph Convolutional Networks

https://github.com/cisnlp/graph-align

공식 코드

Graph Algorithms for Multiparallel Word Alignment

https://github.com/cl-anssi/networksourceseparation

공식 코드

A source separation approach to temporal graph modelling for computer networks

https://github.com/claudmor/multi_task_multi_class_neural_directed_link_prediction

공식 코드

Multi-Class and Multi-Task Strategies for Neural Directed Link Prediction

https://github.com/cods-gcs/kgnet

공식 코드

Towards a GML-Enabled Knowledge Graph Platform

https://github.com/cods-gcs/kgtosa

공식 코드

Task-Oriented GNNs Training on Large Knowledge Graphs for Accurate and Efficient Modeling

https://github.com/colinneverland/staa

공식 코드

Adaptive Spatiotemporal Augmentation for Improving Dynamic Graph Learning

https://github.com/cominsys/ExEm

공식 코드

ExEm: Expert Embedding using dominating set theory with deep learning approaches

https://github.com/congasix/DeepNC

공식 코드

DeepNC: Deep Generative Network Completion

https://github.com/contextkit/mydigitalfootprint

공식 코드

MyDigitalFootprint: an extensive context dataset for pervasive computing applications at the edge

https://github.com/cooper-org/cooper

공식 코드

Novel Node Category Detection Under Subpopulation Shift

https://github.com/cooperativenetworklearning/cooperative-network-learning

공식 코드

Cooperative Network Learning for Large-Scale and Decentralized Graphs

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