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Graph Neural Network

Papers

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Showing 1501–1525 of 3598 papers

TitleStatusHype
Few-shot fault diagnosis based on multi-scale graph convolution filtering for industry—0
Multiscale Spatio-Temporal Enhanced Short-term Load Forecasting of Electric Vehicle Charging Stations—0
DeepHGNN: Study of Graph Neural Network based Forecasting Methods for Hierarchically Related Multivariate Time Series—0
LSPI: Heterogeneous Graph Neural Network Classification Aggregation Algorithm Based on Size Neighbor Path IdentificationCode0
SIG: Efficient Self-Interpretable Graph Neural Network for Continuous-time Dynamic GraphsCode0
A Vlogger-augmented Graph Neural Network Model for Micro-video RecommendationCode0
Rethinking Pruning for Backdoor Mitigation: An Optimization Perspective—0
Survey of Graph Neural Network for Internet of Things and NextG Networks—0
R-ODE: Ricci Curvature Tells When You Will be Informed—0
Graph Neural Networks on Quantum Computers—0
SmoothGNN: Smoothing-aware GNN for Unsupervised Node Anomaly Detection—0
Enhancing Sustainable Urban Mobility Prediction with Telecom Data: A Spatio-Temporal Framework ApproachCode0
Differentiable Cluster Graph Neural Network—0
Learning from Linear Algebra: A Graph Neural Network Approach to Preconditioner Design for Conjugate Gradient Solvers—0
Cardinality Estimation on Hyper-relational Knowledge Graphs—0
DFGNN: Dual-frequency Graph Neural Network for Sign-aware Feedback—0
SATSense: Multi-Satellite Collaborative Framework for Spectrum Sensing—0
MeMo: Meaningful, Modular Controllers via Noise Injection—0
Bond Graphs for multi-physics informed Neural Networks for multi-variate time series—0
Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class PartitionCode0
LOGIN: A Large Language Model Consulted Graph Neural Network Training FrameworkCode0
Floor-Plan-aided Indoor Localization: Zero-Shot Learning Framework, Data Sets, and PrototypeCode0
Rumor Detection on Social Media with Reinforcement Learning-based Key Propagation Graph Generator—0
How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashingCode0
Presentations are not always linear! GNN meets LLM for Document-to-Presentation Transformation with Attribution—0
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Benchmark Results

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