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Graph Attention

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

https://github.com/yongchao-liu/gipa

공식 코드

GIPA: General Information Propagation Algorithm for Graph Learning

https://github.com/yongduosui/cal

공식 코드

Causal Attention for Interpretable and Generalizable Graph Classification

https://github.com/youqingxiaozhua/deepternary

공식 코드

SE(3)-Equivariant Ternary Complex Prediction Towards Target Protein Degradation

https://github.com/yuanyuanlei-nlp/conspiracy_theories_emnlp_2023

공식 코드

Identifying Conspiracy Theories News based on Event Relation Graph

https://github.com/yuanyuanlei-nlp/sentence_level_media_bias_naacl_2024

공식 코드

Sentence-level Media Bias Analysis with Event Relation Graph

https://github.com/yuehu9/dsab-detecting-socially-abnormal-drving-behaviors

공식 코드

Detecting Socially Abnormal Highway Driving Behaviors via Recurrent Graph Attention Networks

https://github.com/yueming-yin/gafse

공식 코드

An open unified deep graph learning framework for discovering drug leads

https://github.com/yulun-rayn/SGAnCP4ADD

공식 코드

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

https://github.com/yulun-rayn/dgapn

공식 코드

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

https://github.com/zahiriddin-rustamov/gat-rwos

공식 코드

GAT-RWOS: Graph Attention-Guided Random Walk Oversampling for Imbalanced Data Classification

https://github.com/zahrag/GAIN

공식 코드

Graph Representation Learning for Road Type Classification

https://github.com/zaiwen/hncl-dti

공식 코드

A Heterogeneous Network-based Contrastive Learning Approach for Predicting Drug-Target Interaction

https://github.com/zcaicaros/tbgat

공식 코드

Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem

https://github.com/zcrwind/tgg-pytorch

공식 코드

TGG: Transferable Graph Generation for Zero-shot and Few-shot Learning

https://github.com/zhang-jinghua/dbc-fscil

공식 코드

A Forward and Backward Compatible Framework for Few-shot Class-incremental Pill Recognition

https://github.com/zhangdatalab/chgat

공식 코드

For the Underrepresented in Gender Bias Research: Chinese Name Gender Prediction with Heterogeneous Graph Attention Network

https://github.com/zhangtia16/licap

공식 코드

Label Informed Contrastive Pretraining for Node Importance Estimation on Knowledge Graphs

https://github.com/zhengfang1997/Unlimited-Neighborhood-Interaction-for-Heterogeneous-Trajectory-Prediction

공식 코드

Unlimited Neighborhood Interaction for Heterogeneous Trajectory Prediction

https://github.com/zhiyongc/Graph_Convolutional_LSTM

공식 코드

Graph Neural Network for Traffic Forecasting: A Survey

https://github.com/zhiyongc/Seattle-Loop-Data

공식 코드

Graph Neural Network for Traffic Forecasting: A Survey

https://github.com/zhongpeixiang/KET

공식 코드

Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations

https://github.com/zhouc20/k-transformer

공식 코드

On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers

https://github.com/zhouxianchen/robustGAT

공식 코드

A Robust graph attention network with dynamic adjusted Graph

https://github.com/zhurboo/RAGA

공식 코드

RAGA: Relation-aware Graph Attention Networks for Global Entity Alignment

https://github.com/zipging/darlc

공식 코드

Dual Advancement of Representation Learning and Clustering for Sparse and Noisy Images

https://github.com/zixianreid/semantic_graph_code_code_clone

공식 코드

AST-Enhanced or AST-Overloaded? The Surprising Impact of Hybrid Graph Representations on Code Clone Detection

https://github.com/zju3dv/OnePose

공식 코드

OnePose: One-Shot Object Pose Estimation without CAD Models

https://github.com/zjulihongxin/memonav

공식 코드

MemoNav: Working Memory Model for Visual Navigation

https://github.com/zshicode/gnn-attcl-protein

공식 코드

Graph neural networks and attention-based CNN-LSTM for protein classification

https://github.com/zzr8066/graphdoc

공식 코드

Multimodal Pre-training Based on Graph Attention Network for Document Understanding

https://github.com/2023-MindSpore-1/ms-code-218/tree/main/m2n

M2N: Mesh Movement Networks for PDE Solvers

https://github.com/404nofound/gat

Graph Attention Networks

https://github.com/4pygmalion/GAT_tensorflow

Graph Attention Networks

https://github.com/AI-Guru/pointcloud_experiments

GAPNet: Graph Attention based Point Neural Network for Exploiting Local Feature of Point Cloud

https://github.com/Anak2016/GAT

Graph Attention Networks

https://github.com/AngusMonroe/GAT-pytorch

Graph Attention Networks

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