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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/QingruZhang/Thanos

공식 코드

A Biased Graph Neural Network Sampler with Near-Optimal Regret

https://github.com/RAIL-group/RAIL-group-software/tree/main/modules/lsp_gnn

공식 코드

Improving Reliable Navigation under Uncertainty via Predictions Informed by Non-Local Information

https://github.com/RManLuo/CP-GNN

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Detecting Communities from Heterogeneous Graphs: A Context Path-based Graph Neural Network Model

https://github.com/RManLuo/gfm-rag

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GFM-RAG: Graph Foundation Model for Retrieval Augmented Generation

https://github.com/RRRussell/CauGNN/tree/main/MTS_TEGNN-master

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Multivariate Time Series Forecasting with Transfer Entropy Graph

https://github.com/RUCAIBox/CRSLab

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CRSLab: An Open-Source Toolkit for Building Conversational Recommender System

https://github.com/RUNCSP/RUN-CSP

공식 코드

Graph Neural Networks for Maximum Constraint Satisfaction

https://github.com/RexYing/gnn-model-explainer

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GNNExplainer: Generating Explanations for Graph Neural Networks

https://github.com/RingBDStack/HAE

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Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks

https://github.com/RingBDStack/KPGNN

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Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs

https://github.com/RingBDStack/SUGAR

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SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism

https://github.com/RobertoMCA/keyphrase-extraction-with-graph-embeddings

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Enhancing Keyphrase Extraction from Long Scientific Documents using Graph Embeddings

https://github.com/RobinLu1209/Geometer

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Geometer: Graph Few-Shot Class-Incremental Learning via Prototype Representation

https://github.com/Rose-STL-Lab/HDR-IL

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Deep Imitation Learning for Bimanual Robotic Manipulation

https://github.com/RuihongQiu/GAG

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GAG: Global Attributed Graph Neural Network for Streaming Session-based Recommendation

https://github.com/Scarecrow0/BGNN-SGG

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Bipartite Graph Network with Adaptive Message Passing for Unbiased Scene Graph Generation

https://github.com/SenticNet/conv-emotion

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DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation

https://github.com/ShaohuiLiu/GNN_OPF_electricity_market

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Topology-aware Graph Neural Networks for Learning Feasible and Adaptive ac-OPF Solutions

https://github.com/Sheng-J/DOM-Q-NET

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DOM-Q-NET: Grounded RL on Structured Language

https://github.com/Shuijing725/CrowdNav_Prediction_AttnGraph

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Intention Aware Robot Crowd Navigation with Attention-Based Interaction Graph

https://github.com/ShunChengWu/3DSSG

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SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences

https://github.com/ShunChengWu/SceneGraphFusion

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SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences

https://github.com/Sinwang404/DeepDDs

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DeepDDS: deep graph neural network with attention mechanism to predict synergistic drug combinations

https://github.com/SophieZheng998/MaskDroid

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MASKDROID: Robust Android Malware Detection with Masked Graph Representations

https://github.com/SpaceLearner/SessionRec-pytorch

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Learning Multi-granularity User Intent Unit for Session-based Recommendation

https://github.com/SsGood/NFGNN

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Node-oriented Spectral Filtering for Graph Neural Networks

https://github.com/SunJiamei/few-shot-lrp-guided

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Explanation-Guided Training for Cross-Domain Few-Shot Classification

https://github.com/THUDM/CogQA

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Cognitive Graph for Multi-Hop Reading Comprehension at Scale

https://github.com/THUDM/GCC

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GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training

https://github.com/TencentGameMate/gnn_cross_lingual

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Cross-lingual Text Classification with Heterogeneous Graph Neural Network

https://github.com/TheLeprechaun25/neural-improvement-heuristics

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Neural Improvement Heuristics for Graph Combinatorial Optimization Problems

https://github.com/TmacMai/ARGF_multimodal_fusion

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Modality to Modality Translation: An Adversarial Representation Learning and Graph Fusion Network for Multimodal Fusion

https://github.com/UNIC-Lab/LOGNN

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Scalable Resource Management for Dynamic MEC: An Unsupervised Link-Output Graph Neural Network Approach

https://github.com/USC-InfoLab/NeuroGNN

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Dynamic GNNs for Precise Seizure Detection and Classification from EEG Data

https://github.com/USC-InfoLab/busyness-graph-neural-network

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Learning Dynamic Graphs from All Contextual Information for Accurate Point-of-Interest Visit Forecasting

https://github.com/VITA-Group/Deep_GCN_Benchmarking

공식 코드

EEGNN: Edge Enhanced Graph Neural Network with a Bayesian Nonparametric Graph Model

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