GitHub topics: dynamic-gnns
sybeam27/Periodic-Event-Graphs
Dynamic Periodic Event Graphs for Multivariate Time Series Pattern Prediction (PeerJ Computer Science)
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Prot10/DyGNN
Dynamic Graph Neural Networks to Predict Collaborations between Authors
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USC-InfoLab/busyness-graph-neural-network
Busyness Graph Neural Network (BysGNN): A framework for accurate Point-of-Interest visit forecasting using dynamic graphs that capture spatial, temporal, semantic, and taxonomic contexts. Presented at ACM SIGSPATIAL 2023, this repository includes code, baselines, and experiments.
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USC-InfoLab/NeuroGNN
NeuroGNN is a state-of-the-art framework for precise seizure detection and classification from EEG data. It employs dynamic Graph Neural Networks (GNNs) to capture intricate spatial, temporal, semantic, and taxonomic correlations between EEG electrode locations and brain regions, resulting in improved accuracy. Presented at PAKDD '24.
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