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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/dojeon-ai/strap

공식 코드

ST-RAP: A Spatio-Temporal Framework for Real Estate Appraisal

https://github.com/draym28/lsgnn

공식 코드

LSGNN: Towards General Graph Neural Network in Node Classification by Local Similarity

https://github.com/drmeerkat/Deep-Graph-Value-Network

공식 코드

Towards Sample Efficient Agents through Algorithmic Alignment

https://github.com/drownfish19/corrstn

공식 코드

A Correlation Information-based Spatiotemporal Network for Traffic Flow Forecasting

https://github.com/ds3lab/dyhgn

공식 코드

Modelling graph dynamics in fraud detection with "Attention"

https://github.com/ds4dm/learn2comparenodes

공식 코드

Learning to Compare Nodes in Branch and Bound with Graph Neural Networks

https://github.com/ds4sd/molgrapher

공식 코드

MolGrapher: Graph-based Visual Recognition of Chemical Structures

https://github.com/dsail-skku/multimodal-aphasia-type-detection_emnlp_2023

공식 코드

Learning Co-Speech Gesture for Multimodal Aphasia Type Detection

https://github.com/dshi3553usyd/curvature_enhanced_graph_convolution

공식 코드

How Curvature Enhance the Adaptation Power of Framelet GCNs

https://github.com/dumingsen/calonet

공식 코드

Causal and Local Correlations Based Network for Multivariate Time Series Classification

https://github.com/dyu62/deep-domain-generalization

공식 코드

Deep Spatial Domain Generalization

https://github.com/dyu62/multisource-spatial-point-prediction

공식 코드

Self-consistent Deep Geometric Learning for Heterogeneous Multi-source Spatial Point Data Prediction

https://github.com/dzambon/NGAR

공식 코드

Autoregressive Models for Sequences of Graphs

https://github.com/dzambon/graph-random-neural-features

공식 코드

Graph Random Neural Features for Distance-Preserving Graph Representations

https://github.com/eBay/xFraud

공식 코드

xFraud: Explainable Fraud Transaction Detection

https://github.com/earth-intelligence-lab/localizedweathergnn

공식 코드

Local Off-Grid Weather Forecasting with Multi-Modal Earth Observation Data

https://github.com/ebonilla/VGCN

공식 코드

Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings

https://github.com/ecml-peagnn/PEAGNN

공식 코드

Metapath- and Entity-aware Graph Neural Network for Recommendation

https://github.com/ecnu-text-computing/dppdcc

공식 코드

Predicting Scientific Impact Through Diffusion, Conformity, and Contribution Disentanglement

https://github.com/ecnu-text-computing/h2cgl

공식 코드

H2CGL: Modeling Dynamics of Citation Network for Impact Prediction

https://github.com/edgarsmdn/gh-gnn

공식 코드

Gibbs-Helmholtz Graph Neural Network: capturing the temperature dependency of activity coefficients at infinite dilution

https://github.com/edgeslab/IDE-Net

공식 코드

Inferring Individual Direct Causal Effects Under Heterogeneous Peer Influence

https://github.com/edisonleeeee/sat

공식 코드

Spectral Adversarial Training for Robust Graph Neural Network

https://github.com/ee1s/nirgnn

공식 코드

Dual Intent Enhanced Graph Neural Network for Session-based New Item Recommendation

https://github.com/eecrazy/ConstructingNEEG_IJCAI_2018

공식 코드

Constructing Narrative Event Evolutionary Graph for Script Event Prediction

https://github.com/ehtesam3154/biomarl

공식 코드

Biological Pathway Guided Gene Selection Through Collaborative Reinforcement Learning

https://github.com/eidoslab/wignet

공식 코드

WiGNet: Windowed Vision Graph Neural Network

https://github.com/ejwww/tangnn

공식 코드

TANGNN: a Concise, Scalable and Effective Graph Neural Networks with Top-m Attention Mechanism for Graph Representation Learning

https://github.com/emalgorithm/directed-graph-neural-network

공식 코드

Edge Directionality Improves Learning on Heterophilic Graphs

https://github.com/enoche/igt-wsdm23

공식 코드

Inductive Graph Transformer for Delivery Time Estimation

https://github.com/enyandai/segnn

공식 코드

Towards Self-Explainable Graph Neural Network

https://github.com/ermongroup/GraphScoreMatching

공식 코드

Permutation Invariant Graph Generation via Score-Based Generative Modeling

https://github.com/event-ahu/efv_event_classification

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Learning Bottleneck Transformer for Event Image-Voxel Feature Fusion based Classification

https://github.com/event-ahu/vct_remote_sensing_change_detection

공식 코드

VcT: Visual change Transformer for Remote Sensing Image Change Detection

https://github.com/exploration-lab/cogmen

공식 코드

COGMEN: COntextualized GNN based Multimodal Emotion recognitioN

https://github.com/fabecode/GraphML-FHE

공식 코드

Privacy-Preserving Graph-Based Machine Learning with Fully Homomorphic Encryption for Collaborative Anti-Money Laundering

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