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Graph Neural Network
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/roth-andreas/pprgnn
공식 코드Transforming PageRank into an Infinite-Depth Graph Neural Network
https://github.com/rrgitan/LEGNN
공식 코드Training a Label-Noise-Resistant GNN with Reduced Complexity
https://github.com/rrr-uom-projects/contour_auto_qatool
공식 코드Automatic identification of segmentation errors for radiotherapy using geometric learning
https://github.com/rrrussell/caugnn
공식 코드Multivariate Time Series Forecasting with Transfer Entropy Graph
https://github.com/rsalganik1123/facctrec2022
공식 코드Analyzing the Effect of Sampling in GNNs on Individual Fairness
https://github.com/rsinghlab/gnn-tumor-seg
공식 코드A Joint Graph and Image Convolution Network for Automatic Brain Tumor Segmentation
https://github.com/rtealwitter/openstreets
공식 코드I Open at the Close: A Deep Reinforcement Learning Evaluation of Open Streets Initiatives
https://github.com/rucaibox/cogcl
공식 코드Enhancing Graph Contrastive Learning with Reliable and Informative Augmentation for Recommendation
https://github.com/rucaibox/recbole2.0
공식 코드RecBole 2.0: Towards a More Up-to-Date Recommendation Library
https://github.com/rucaibox/safe
공식 코드https://github.com/ruijie-wang-uzh/gnn2r
공식 코드GNN2R: Weakly-Supervised Rationale-Providing Question Answering over Knowledge Graphs
https://github.com/ruizehan/par
공식 코드https://github.com/ruizhang-ai/SIGN-Detecting-Beneficial-Feature-Interactions-for-Recommender-Systems
공식 코드Detecting Beneficial Feature Interactions for Recommender Systems
https://github.com/runzewang/IST-SQL
공식 코드Tracking Interaction States for Multi-Turn Text-to-SQL Semantic Parsing
https://github.com/russellizadi/ssp
공식 코드Optimization of Graph Neural Networks with Natural Gradient Descent
https://github.com/rusty1s/deep-graph-matching-consensus
공식 코드https://github.com/rusty1s/pytorch_geometric
공식 코드https://github.com/ruyilian/checkerpose
공식 코드https://github.com/ryanliu30/hierarchicalgnn
공식 코드Hierarchical Graph Neural Networks for Particle Track Reconstruction
https://github.com/sYeaLumin/SketchGNN
공식 코드SketchGNN: Semantic Sketch Segmentation with Graph Neural Networks
https://github.com/safe-graph/DGFraud
공식 코드Alleviating the Inconsistency Problem of Applying Graph Neural Network to Fraud Detection
https://github.com/safe-graph/RioGNN
공식 코드Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks
https://github.com/safreita1/malnet-graph
공식 코드https://github.com/sanxing-chen/linking-tale
공식 코드https://github.com/sara-silvaad/connectome_gcl
공식 코드https://github.com/sathwikchadaga/failure-cascade
공식 코드Power Failure Cascade Prediction using Graph Neural Networks
https://github.com/scfischer/dirk-et-al-2022
공식 코드Recognition and reconstruction of cell differentiation patterns with deep learning
https://github.com/schmidt-ju/scene
공식 코드SCENE: Reasoning about Traffic Scenes using Heterogeneous Graph Neural Networks
https://github.com/scofield666/mbssl
공식 코드https://github.com/scottjiao/slotgat_icml23
공식 코드SlotGAT: Slot-based Message Passing for Heterogeneous Graph Neural Network
https://github.com/sczhou/IGNN
공식 코드Cross-Scale Internal Graph Neural Network for Image Super-Resolution
https://github.com/seaocn/motif-backdoor
공식 코드Motif-Backdoor: Rethinking the Backdoor Attack on Graph Neural Networks via Motifs
https://github.com/seijimaekawa/a2dug
공식 코드A Simple and Scalable Graph Neural Network for Large Directed Graphs
https://github.com/selgroup/hisevent
공식 코드Hierarchical and Incremental Structural Entropy Minimization for Unsupervised Social Event Detection
https://github.com/seonghyun26/nba-gnn
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.