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Graph Neural Network

Papers

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Showing 901–925 of 3598 papers

TitleStatusHype
A Federated Parameter Aggregation Method for Node Classification Tasks with Different Graph Network Structures—0
Rumor Detection with a novel graph neural network approach—0
Cascading Blackout Severity Prediction with Statistically-Augmented Graph Neural Networks—0
iSpLib: A Library for Accelerating Graph Neural Networks using Auto-tuned Sparse OperationsCode0
Knowledge-Enhanced Recommendation with User-Centric Subgraph NetworkCode0
Graph Neural Network for Crawling Target Nodes in Social Networks—0
Unifews: Unified Entry-Wise Sparsification for Efficient Graph Neural Network—0
Graph Neural Network for Neutrino Physics Event Reconstruction—0
Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series Imputation—0
Integrating Physics Inspired Features with Graph ConvolutionCode0
Dual-Channel Multiplex Graph Neural Networks for Recommendation—0
Graph Machine Learning based Doubly Robust Estimator for Network Causal Effects—0
Multi-Relational Graph Neural Network for Out-of-Domain Link Prediction—0
DynamicGlue: Epipolar and Time-Informed Data Association in Dynamic Environments using Graph Neural Networks—0
ECRC: Emotion-Causality Recognition in Korean Conversation for GCN—0
stMCDI: Masked Conditional Diffusion Model with Graph Neural Network for Spatial Transcriptomics Data Imputation—0
Discovering Invariant Neighborhood Patterns for Heterophilic Graphs—0
Generation is better than Modification: Combating High Class Homophily Variance in Graph Anomaly Detection—0
Thermal Earth Model for the Conterminous United States Using an Interpolative Physics-Informed Graph Neural Network (InterPIGNN)—0
From Chaos to Clarity: Time Series Anomaly Detection in Astronomical ObservationsCode0
BG-HGNN: Toward Scalable and Efficient Heterogeneous Graph Neural Network—0
Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network Research—0
Iterative Graph Neural Network Enhancement via Frequent Subgraph Mining of Explanations—0
SiGNN: A Spike-induced Graph Neural Network for Dynamic Graph Representation Learning—0
Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic GraphsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1air0S1—Unverified