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Graph Neural Network

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/LinXueyuanStdio/EchoEA

공식 코드

EchoEA: Echo Information between Entities and Relations for Entity Alignment

https://github.com/LiuHeBJTU/GLAM

공식 코드

Joint Graph Learning and Matching for Semantic Feature Correspondence

https://github.com/Lixy1997/Group-WSSS

공식 코드

Group-Wise Semantic Mining for Weakly Supervised Semantic Segmentation

https://github.com/Lollo0900/Plumbed_3-Manifolds

공식 코드

Detecting Homeomorphic 3-manifolds via Graph Neural Networks

https://github.com/LuChang-CS/sherbet

공식 코드

Self-Supervised Graph Learning with Hyperbolic Embedding for Temporal Health Event Prediction

https://github.com/MIT-SPARK/PD-MeshNet

공식 코드

Primal-Dual Mesh Convolutional Neural Networks

https://github.com/MaKaili/Contrast-Reg

공식 코드

Calibrating and Improving Graph Contrastive Learning

https://github.com/MaiqiVerse/AutoGNR

공식 코드

Automated Heterogeneous Network learning with Non-Recursive Message Passing

https://github.com/ManlioWu/ESTAG

공식 코드

Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics

https://github.com/Microsoft/PDP-Solver

공식 코드

PDP: A General Neural Framework for Learning Constraint Satisfaction Solvers

https://github.com/MikeZChi/GSPHAR

공식 코드

Graph Signal Processing for Global Stock Market Realized Volatility Forecasting

https://github.com/Mobzhang/PT-DGNN

공식 코드

Pre-Training on Dynamic Graph Neural Networks

https://github.com/MountainChenCad/HRRPGraphNet

공식 코드

HRRPGraphNet: Make HRRPs to Be Graphs for Efficient Target Recognition

https://github.com/MrVPlusOne/LambdaNet

공식 코드

LambdaNet: Probabilistic Type Inference using Graph Neural Networks

https://github.com/MysteryVaibhav/fake_news_semantics

공식 코드

Do Sentence Interactions Matter? Leveraging Sentence Level Representations for Fake News Classification

https://github.com/NSLab-CUK/S-CGIB

공식 코드

Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck

https://github.com/NYUMedML/GNN_for_EHR

공식 코드

Variationally Regularized Graph-based Representation Learning for Electronic Health Records

https://github.com/Nanyuu/TUA

공식 코드

A Targeted Universal Attack on Graph Convolutional Network

https://github.com/NiklasFreymuth/AMBER

공식 코드

Iterative Sizing Field Prediction for Adaptive Mesh Generation From Expert Demonstrations

https://github.com/Nokia-Bell-Labs/olp-gnn

공식 코드

Learning Optimal Linear Precoding for Cell-Free Massive MIMO with GNN

https://github.com/NormXU/Layout2Graph

공식 코드

PARAGRAPH2GRAPH: A GNN-based framework for layout paragraph analysis

https://github.com/Open-Catalyst-Project/Open-Catalyst-Dataset

공식 코드

The Open Catalyst 2020 (OC20) Dataset and Community Challenges

https://github.com/Open-Catalyst-Project/ocp

공식 코드

The Open Catalyst 2020 (OC20) Dataset and Community Challenges

https://github.com/PASSIONLab/CAGNET

공식 코드

Reducing Communication in Graph Neural Network Training

https://github.com/PASSIONLab/gnn_training

공식 코드

Reducing Communication in Graph Neural Network Training

https://github.com/PIK-ICoNe/DBGNN_paper-companion

공식 코드

Dirac--Bianconi Graph Neural Networks -- Enabling Non-Diffusive Long-Range Graph Predictions

https://github.com/PaddlePaddle/PGL

공식 코드

Graph4Rec: A Universal Toolkit with Graph Neural Networks for Recommender Systems

https://github.com/PaddlePaddle/PGL/tree/main/ogb_examples/nodeproppred/unimp

공식 코드

Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification

https://github.com/PaddlePaddle/PaddleSpatial/tree/main/research/SEENet

공식 코드

Multi-Temporal Relationship Inference in Urban Areas

https://github.com/PaddlePaddle/PaddleSpatial/tree/main/research/SHGNN

공식 코드

Spatial Heterophily Aware Graph Neural Networks

https://github.com/PengBoXiangShang/multigraph_transformer

공식 코드

Multi-Graph Transformer for Free-Hand Sketch Recognition

https://github.com/Pengxin-Guo/HGNN

공식 코드

Deep Multi-Task Augmented Feature Learning via Hierarchical Graph Neural Network

https://github.com/Peterbotliang/NEBP-Cooperative-Localization

공식 코드

Neural Enhanced Belief Propagation for Cooperative Localization

https://github.com/PlusRoss/Hy-Transformer

공식 코드

Improving Hyper-Relational Knowledge Graph Completion

https://github.com/QTrkX/qtrkx-gnn-tracking

공식 코드

Hybrid Quantum Classical Graph Neural Networks for Particle Track Reconstruction

https://github.com/QiWang98/PromptCGL

공식 코드

Prompt-Driven Continual Graph Learning

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