https://github.com/anacletolab/grape
공식 코드GRAPE for Fast and Scalable Graph Processing and random walk-based Embedding
Papers with Code 아카이브
Link Prediction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 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/andyjzhao/wsdm23-gsr
공식 코드Self-Supervised Graph Structure Refinement for Graph Neural Networks
https://github.com/andyweizhao/graphs-normed-spaces
공식 코드https://github.com/anilakash/indkgc
공식 코드Inductive Knowledge Graph Completion with GNNs and Rules: An Analysis
https://github.com/ankush9812/aviation-question-answer-pairs
공식 코드https://github.com/ankush9812/knowledge-infusion-in-lm-for-qa
공식 코드https://github.com/ansonb/hopfe
공식 코드HopfE: Knowledge Graph Representation Learning using Inverse Hopf Fibrations
https://github.com/anthbapt/multixrank
공식 코드Universal Multilayer Network Exploration by Random Walk with Restart
https://github.com/antoniopurificato/sheaf4rec
공식 코드Sheaf4Rec: Sheaf Neural Networks for Graph-based Recommender Systems
https://github.com/apoorvumang/kgt5
공식 코드Sequence-to-Sequence Knowledge Graph Completion and Question Answering
https://github.com/april-tools/gekcs
공식 코드How to Turn Your Knowledge Graph Embeddings into Generative Models
https://github.com/arash-dehghan/EmbeddingComplexNetworks
공식 코드https://github.com/aravindsankar28/DySAT
공식 코드Dynamic Graph Representation Learning via Self-Attention Networks
https://github.com/arbenson/ScHoLP-Tutorial
공식 코드https://github.com/arbenson/cflp
공식 코드https://github.com/arianemarandon/linkpredconf
공식 코드https://github.com/arjunsubramonian/link_bias_amplification
공식 코드Networked Inequality: Preferential Attachment Bias in Graph Neural Network Link Prediction
https://github.com/artessay/ragraph
공식 코드RAGraph: A General Retrieval-Augmented Graph Learning Framework
https://github.com/artificial-scientist-lab/futureofaiviaai
공식 코드https://github.com/arvindh75/cafin
공식 코드https://github.com/aryopg/biokge
공식 코드https://github.com/ashutoshaay26/Relational-Boosted-Bandits
공식 코드https://github.com/astroming/GNNHE
공식 코드Can GNNs Learn Link Heuristics? A Concise Review and Evaluation of Link Prediction Methods
https://github.com/ayyyq/tara
공식 코드An AMR-based Link Prediction Approach for Document-level Event Argument Extraction
https://github.com/badalyananna/hycosbm
공식 코드https://github.com/baharefatemi/ReAlE
공식 코드https://github.com/banghonor/disco
공식 코드https://github.com/barbara20901/cluster-link-prediction
공식 코드A Cluster-Based Trip Prediction Graph Neural Network Model for Bike Sharing Systems
https://github.com/batjandra/TGNv2-NeurReps
공식 코드Enhancing the Expressivity of Temporal Graph Networks through Source-Target Identification
https://github.com/bayrameda/MrAP
공식 코드Node Attribute Completion in Knowledge Graphs with Multi-Relational Propagation
https://github.com/bdi-lab/bive
공식 코드Learning Representations of Bi-level Knowledge Graphs for Reasoning beyond Link Prediction
https://github.com/bengutteridge/drew
공식 코드https://github.com/bhagya-hettige/GLACE
공식 코드https://github.com/bhushank/kge-rl
공식 코드Analysis of the Impact of Negative Sampling on Link Prediction in Knowledge Graphs
https://github.com/billy-inn/HRERE
공식 코드Connecting Language and Knowledge with Heterogeneous Representations for Neural Relation Extraction
https://github.com/biochunan/asep-dataset
공식 코드AsEP: Benchmarking Deep Learning Methods for Antibody-specific Epitope Prediction
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.