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Traffic Flow Prediction via Spatial Temporal Graph Neural Network
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What points at this work
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DAHGN: Degree-Aware Heterogeneous Graph Neural Network
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A graph-based approach for traffic prediction using similarity and causal relations between nodes
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Backbone-based Dynamic Spatio-Temporal Graph Neural Network for epidemic forecasting
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Towards hour-level crime prediction: A neural attentive framework with spatial–temporal-categorical fusion
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Deep multi-view graph-based network for citywide ride-hailing demand prediction
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DSTF: A Diversified Spatio-Temporal Feature Extraction Model for traffic flow prediction
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A noval Dual-Parameter Structural Model with Enhanced traffic flow representations
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ST-CML: A contrastive meta learning framework for spatio-temporal graph few-shot learning with cross-city transfer
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Subgraph-aware graph structure revision for spatial–temporal graph modeling
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Adaptive Decision Spatio-temporal neural ODE for traffic flow forecasting with Multi-Kernel Temporal Dynamic Dilation Convolution
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PDG2Seq: Periodic Dynamic Graph to Sequence Model for Traffic Flow Prediction
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Trajectory prediction of seagoing ships in dynamic traffic scenes via a gated spatio-temporal graph aggregation network
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Multi-head graph contrastive learning with hop augmentation for node classification
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Traffic Anomaly Detection based on Spatio-Temporal Hypergraph Convolution Neural Networks
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A unified traffic flow prediction model considering node differences, spatio-temporal features, and local-global dynamics
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Light attention-based neural networks for traffic flow prediction
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Exploring to predict the tipping points in traffic flow: A lightweight spatio-temporal information-enhanced neural point process approach
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Artificial intelligence for climate change mitigation and adaptation: A domain-structured review of methods, applications, and research gaps for seven high-impact domains
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Hyper-Flophet: A neural Prophet-based model for traffic flow forecasting in transportation systems
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An efficient encrypted deduplication scheme with security-enhanced proof of ownership in edge computing
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Traffic prediction using artificial intelligence: Review of recent advances and emerging opportunities
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Joint dynamic pruning method for graph neural networks under traffic prediction scenarios
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Ship risk prediction: A methodological study
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Spatio-temporal Graph Convolutional Neural Network for traffic signal prediction in large-scale urban networks
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Comparison of biomedical relationship extraction methods and models for knowledge graph creation
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Deep Learning on Graphs: An Introduction
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Foundations of Deep Learning
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Robust Graph Neural Networks
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Scalable Graph Neural Networks
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Graph Neural Networks for Complex Graphs
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Beyond GNNs: More Deep Models on Graphs
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Graph Neural Networks in Natural Language Processing
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Graph Neural Networks in Computer Vision
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Graph Neural Networks in Data Mining
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Graph Neural Networks in Biochemistry and Health Care
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Advanced Topics in Graph Neural Networks
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Advanced Applications in Graph Neural Networks
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Adaptable graph region for optimizing performance in dynamic system long-term forecasting via time-aware expert
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A multi-modal attention neural network for traffic flow prediction by capturing long-short term sequence correlation
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Spatio-temporal envolutional graph neural network for traffic flow prediction in UAV-based urban traffic monitoring system
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Cross-domain transformer spatial-temporal fusion network for traffic flow forecasting
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Pretraining-improved Spatiotemporal graph network for the generalization performance enhancement of traffic forecasting
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STICformer: spatio-temporal intrinsic connections transformer for traffic flow prediction
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Multi-scale spatial-temporal transformer for traffic flow prediction
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An interpretable model based on graph learning for diagnosis of Parkinson’s disease with voice-related EEG
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Correlated load forecasting in active distribution networks using Spatial‐Temporal Synchronous Graph Convolutional Networks
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HD‐Net: A hybrid dynamic spatio‐temporal network for traffic flow prediction
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A Multi‐Graph Attentive Network for Traffic Speed Prediction and Diagnosis
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Population‐Demand‐Congestion Prediction Framework: Traffic Dispersion Through Traffic Prediction Using Population Distribution Based on Mobile Big Data
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Graph Neural Networks for State Estimation in Water Distribution Systems: Application of Supervised and Semisupervised Learning
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A Modeling Method for Complex Traffic Flow on Highways Based on the Fusion of Heterogeneous Data from Multiple Sensors
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The prediction of contact force networks in granular materials based on graph neural networks
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A joint missing power data recovery method based on the spatiotemporal correlation of multiple wind farms
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Challenges and improvements in deep learning for traffic prediction
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Conflict forecasting with event data and spatio-temporal graph convolutional networks
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Geospatial analysis of crime patterns and hotspots for crime prevention using deep learning algorithms
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Spatio-Temporal Prediction of Fine-Grained Origin-Destination Matrices with Applications in Ridesharing
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Machine-learning-enabled spatial pattern mining: evaluating the impact of imperfect inputs
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Learning dynamic relational heterogeneity for spatiotemporal prediction with geographical meta-knowledge
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Spatio-temporal graph attention networks for traffic prediction
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Short-term traffic flow prediction via weight optimization of composite models
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