On the public citation graph

3DGCN: 3-Dimensional Dynamic Graph Convolutional Network for Citywide Crowd Flow Prediction

0 signed · 91 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/cmdc.201900458openalex-snapshot
Enhanced Deep‐Learning Prediction of Molecular Properties via Augmentation of Bond Topology
inferredcites →https://doi.org/10.1016/j.acha.2010.04.005openalex-snapshot
Wavelets on graphs via spectral graph theory
inferredcites →https://doi.org/10.1016/j.aiopen.2021.01.001openalex-snapshot
Graph neural networks: A review of methods and applications
inferredcites →https://doi.org/10.1016/j.neucom.2015.12.013openalex-snapshot
A distributed spatial–temporal weighted model on MapReduce for short-term traffic flow forecasting
inferredcites →https://doi.org/10.1016/j.patcog.2019.107000openalex-snapshot
Dynamic graph convolutional networks
inferredcites →https://doi.org/10.1109/5.726791openalex-snapshot
Gradient-based learning applied to document recognition
inferredcites →https://doi.org/10.1109/iske.2017.8258813openalex-snapshot
Traffic flow forecasting based on hybrid deep learning framework
inferredcites →https://doi.org/10.1109/msp.2012.2235192openalex-snapshot
The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains
inferredcites →https://doi.org/10.1109/tits.2013.2247040openalex-snapshot
Short-Term Traffic Flow Forecasting: An Experimental Comparison of Time-Series Analysis and Supervised Learning
inferredcites →https://doi.org/10.1109/tits.2014.2345663openalex-snapshot
Traffic Flow Prediction With Big Data: A Deep Learning Approach
inferredcites →https://doi.org/10.1109/tkde.2014.2345405openalex-snapshot
Discovering Urban Functional Zones Using Latent Activity Trajectories
inferredcites →https://doi.org/10.1109/tkde.2019.2891537openalex-snapshot
Flow Prediction in Spatio-Temporal Networks Based on Multitask Deep Learning
inferredcites →https://doi.org/10.1109/tpami.2012.59openalex-snapshot
3D Convolutional Neural Networks for Human Action Recognition
inferredcites →https://doi.org/10.1145/2750858.2804277openalex-snapshot
CityMomentum
inferredcites →https://doi.org/10.1145/2996913.2996934openalex-snapshot
FCCF
inferredcites →https://doi.org/10.1145/2996913.2997016openalex-snapshot
DNN-based prediction model for spatio-temporal data
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1145/3193077.3193082openalex-snapshot
Spatio-Temporal Recurrent Convolutional Networks for Citywide Short-term Crowd Flows Prediction
inferredcites →https://doi.org/10.1145/3274895.3274896openalex-snapshot
Bike flow prediction with multi-graph convolutional networks
inferredcites →https://doi.org/10.1145/3292500.3330877openalex-snapshot
Origin-Destination Matrix Prediction via Graph Convolution
inferredcites →https://doi.org/10.1145/3292500.3330961openalex-snapshot
Heterogeneous Graph Neural Network
inferredcites →https://doi.org/10.1145/3308558.3313453openalex-snapshot
Understanding Urban Dynamics via State-sharing Hidden Markov Model
inferredcites →https://doi.org/10.1145/3308558.3313562openalex-snapshot
Heterogeneous Graph Attention Network
inferredcites →https://doi.org/10.1145/3366423.3380186openalex-snapshot
Traffic Flow Prediction via Spatial Temporal Graph Neural Network
inferredcites →https://doi.org/10.1145/3394486.3403373openalex-snapshot
Dynamic Heterogeneous Graph Neural Network for Real-time Event Prediction
inferredcites →https://doi.org/10.1145/3411807openalex-snapshot
SUME
inferredcites →https://doi.org/10.1145/3411817openalex-snapshot
Semantic-aware Spatio-temporal App Usage Representation via Graph Convolutional Network
inferredcites →https://doi.org/10.1371/journal.pone.0037027openalex-snapshot
A Tale of Many Cities: Universal Patterns in Human Urban Mobility
inferredcites →https://doi.org/10.1609/aaai.v33i01.33011020openalex-snapshot
DeepSTN+: Context-Aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis
inferredcites →https://doi.org/10.1609/aaai.v33i01.33013656openalex-snapshot
Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting
inferredcites →https://doi.org/10.1609/aaai.v33i01.33015668openalex-snapshot
Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction
inferredcites →https://doi.org/10.24963/ijcai.2018/519openalex-snapshot
Periodic-CRN: A Convolutional Recurrent Model for Crowd Density Prediction with Recurring Periodic Patterns
inferredcites →https://doi.org/10.24963/ijcai.2020/185openalex-snapshot
A Sequential Convolution Network for Population Flow Prediction with Explicitly Correlation Modelling
inferredcites →https://doi.org/10.3141/2024-14openalex-snapshot
Adaptive Seasonal Time Series Models for Forecasting Short-Term Traffic Flow

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4770638openalex-extracted
Gtr: An Explainable Graph Topic-Aware Recommender for Scholarly Document
inferred← citeshttps://doi.org/10.2139/ssrn.4894161openalex-extracted
3d Point Cloud Representation Learning Via Dual Curve-Graph Feature Fusion
inferred← citeshttps://doi.org/10.1002/cpe.70417openalex-snapshot
RoCNet ‐Pro: Nuclear Reactor Pressure Vessel Point Cloud Registration Based on Multi‐Scale Curvature Uncertainty Quantitative Feature Descriptor
inferred← citeshttps://doi.org/10.1007/978-3-031-25900-5_317-1openalex-snapshot
Spatial Analysis
inferred← citeshttps://doi.org/10.1007/978-3-031-92524-5_317openalex-snapshot
Spatial Analysis
inferred← citeshttps://doi.org/10.1007/s00586-026-10117-wopenalex-snapshot
Automated multi-trajectory planning for C1–C2 screw fixation using CT-derived 3D models
inferred← citeshttps://doi.org/10.1007/s10044-025-01519-5openalex-snapshot
Starg2n: a spatial-temporal relevance analysis graph neural network for traffic prediction
inferred← citeshttps://doi.org/10.1007/s10489-022-03324-7openalex-snapshot
A time-dependent attention convolutional LSTM method for traffic flow prediction
inferred← citeshttps://doi.org/10.1007/s10489-025-06371-yopenalex-snapshot
3DGCformer: 3-Dimensional Graph Convolutional transformer for multi-step origin–destination matrix forecasting
inferred← citeshttps://doi.org/10.1007/s10994-025-06990-zopenalex-snapshot
GNN-Based Spatio-Temporal Manifold Learning: An Application of Landslide Prediction
inferred← citeshttps://doi.org/10.1007/s13042-026-03143-zopenalex-snapshot
KAN-based delay-aware dynamic graph networks with spatiotemporal clustering for traffic flow forecasting
inferred← citeshttps://doi.org/10.1007/s40747-024-01768-7openalex-snapshot
A traffic prediction method for missing data scenarios: graph convolutional recurrent ordinary differential equation network
inferred← citeshttps://doi.org/10.1007/s44212-024-00053-9openalex-snapshot
Understanding pedestrian movement using urban sensing technologies: the promise of audio-based sensors
inferred← citeshttps://doi.org/10.1016/j.elerap.2024.101439openalex-snapshot
GTR: An explainable Graph Topic-aware Recommender for scholarly document
inferred← citeshttps://doi.org/10.1016/j.engappai.2025.113161openalex-snapshot
A transferable framework for cross-city forecasting via invariant structural knowledge learning
inferred← citeshttps://doi.org/10.1016/j.eswa.2024.123207openalex-snapshot
Ridesplitting demand prediction via spatiotemporal multi-graph convolutional network
inferred← citeshttps://doi.org/10.1016/j.eswa.2025.130095openalex-snapshot
Exploiting dynamic spatio-temporal correlations for origin-destination demand prediction
inferred← citeshttps://doi.org/10.1016/j.ins.2022.09.053openalex-snapshot
SPRNN: A spatial–temporal recurrent neural network for crowd flow prediction
inferred← citeshttps://doi.org/10.1016/j.jag.2022.102936openalex-snapshot
A review of spatially-explicit GeoAI applications in Urban Geography
inferred← citeshttps://doi.org/10.1016/j.jretconser.2024.104157openalex-snapshot
Reputation vs. price: Sequential recommendations based on cue diagnosticity theory
inferred← citeshttps://doi.org/10.1016/j.neunet.2025.108269openalex-snapshot
A systematic literature review of spatio-temporal graph neural network models for time series forecasting and classification
inferred← citeshttps://doi.org/10.1016/j.tra.2025.104391openalex-snapshot
An attention-based dynamic graph model for on-street parking availability prediction
inferred← citeshttps://doi.org/10.1051/jeos/2025035openalex-snapshot
DKGCN-PCR: Deformable Kernel Graph Convolutional Network for Point Cloud Registration
inferred← citeshttps://doi.org/10.1080/10106049.2023.2252762openalex-snapshot
Graph neural network method for the intelligent selection of river system
inferred← citeshttps://doi.org/10.1080/13658816.2024.2403023openalex-snapshot
A multi-task spatio-temporal fully convolutional model incorporating interaction patterns for traffic flow prediction
inferred← citeshttps://doi.org/10.1109/access.2022.3182497openalex-snapshot
A Graph Neural Network-Based Map Tiles Extraction Method Considering POIs Priority Visualization on Web Map Zoom Dimension
inferred← citeshttps://doi.org/10.1109/cyber67662.2025.11168337openalex-snapshot
6-DoF Grasping Pose Generation Based on Two-Stage Keypoint Regression
inferred← citeshttps://doi.org/10.1109/geoinformatics67279.2025.11173536openalex-snapshot
Application of Geographic Information Artificial Intelligence in Spatio-Temporal Semantic Extraction
inferred← citeshttps://doi.org/10.1109/iccvit67848.2025.11391353openalex-snapshot
RC-OT Flow: Region-Customized Optimal Transport Path for Generative Flow Matching
inferred← citeshttps://doi.org/10.1109/icde55515.2023.00062openalex-snapshot
A Contextual Master-Slave Framework on Urban Region Graph for Urban Village Detection
inferred← citeshttps://doi.org/10.1109/icoias61634.2023.00024openalex-snapshot
Traffic Flow Prediction Based on Spatial-Temporal Sparse Attention Networks
inferred← citeshttps://doi.org/10.1109/itsc57777.2023.10422030openalex-snapshot
On the Importance of Stationarity, Strong Baselines and Benchmarks in Transport Prediction Problems
inferred← citeshttps://doi.org/10.1109/jiot.2023.3281648openalex-snapshot
MG-ASTN: Multigraph Framework With Attentive Spatial–Temporal Networks for Crowd Mobility Prediction
inferred← citeshttps://doi.org/10.1109/pcds68697.2025.11415276openalex-snapshot
DP-ATDN: A Differentially Private Meta Attention-based Temporal Decomposition Network for Time Series Forecasting
inferred← citeshttps://doi.org/10.1109/smartcomp61445.2024.00066openalex-snapshot
Crowd Flow Prediction from Mobile Traces Through Time Series PoI Stay Counts
inferred← citeshttps://doi.org/10.1109/tbdata.2026.3679574openalex-snapshot
Addressing Long-Tailed Spatial and Category Imbalances in Citywide Incident Prediction
inferred← citeshttps://doi.org/10.1109/tits.2022.3220089openalex-snapshot
Spatial-Temporal Position-Aware Graph Convolution Networks for Traffic Flow Forecasting
inferred← citeshttps://doi.org/10.1109/tits.2024.3373507openalex-snapshot
MNAT-Net: Multi-Scale Neighborhood Aggregation Transformer Network for Point Cloud Classification and Segmentation
inferred← citeshttps://doi.org/10.1109/tits.2024.3396382openalex-snapshot
A Freeway Traffic Flow Prediction Model Based on a Generalized Dynamic Spatio-Temporal Graph Convolutional Network
inferred← citeshttps://doi.org/10.1109/tits.2024.3447161openalex-snapshot
AGC-ODE: Adaptive Graph Controlled Neural ODE for Human Mobility Prediction
inferred← citeshttps://doi.org/10.1109/tits.2025.3531665openalex-snapshot
DAGCAN: Decoupled Adaptive Graph Convolution Attention Network for Traffic Forecasting
inferred← citeshttps://doi.org/10.1109/tkde.2023.3333824openalex-snapshot
Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey
inferred← citeshttps://doi.org/10.1109/tkde.2024.3487549openalex-snapshot
Predicting Individual Irregular Mobility via Web Search-Driven Bipartite Graph Neural Networks
inferred← citeshttps://doi.org/10.1109/tkde.2025.3612033openalex-snapshot
Long-Term Urban Flow Prediction Against Data Distribution Shift: A Causal Perspective
inferred← citeshttps://doi.org/10.1109/tvt.2023.3239054openalex-snapshot
Semantics-Aware Dynamic Graph Convolutional Network for Traffic Flow Forecasting
inferred← citeshttps://doi.org/10.1109/tvt.2024.3365213openalex-snapshot
A Spatial-Temporal Gated Hypergraph Convolution Network for Traffic Prediction
inferred← citeshttps://doi.org/10.1109/tvt.2025.3572221openalex-snapshot
Multi-Human Activity Recognition Based on Sequential 4D Point Clouds Using Frequency-Modulated Continuous Wave Radar
inferred← citeshttps://doi.org/10.1145/3565973openalex-snapshot
Graph Neural Networks in IoT: A Survey
inferred← citeshttps://doi.org/10.1145/3580305.3599510openalex-snapshot
Spatial Heterophily Aware Graph Neural Networks
inferred← citeshttps://doi.org/10.1145/3589964openalex-snapshot
Learning the Explainable Semantic Relations via Unified Graph Topic-Disentangled Neural Networks
inferred← citeshttps://doi.org/10.1145/3608954openalex-snapshot
Multi-View Graph Convolutional Networks with Differentiable Node Selection
inferred← citeshttps://doi.org/10.1145/3625101openalex-snapshot
A Multisource Data Fusion-based Heterogeneous Graph Attention Network for Competitor Prediction
inferred← citeshttps://doi.org/10.1145/3625233openalex-snapshot
Demand-driven Urban Facility Visit Prediction
inferred← citeshttps://doi.org/10.1145/3706116openalex-snapshot
Tucker Decomposition-Enhanced Dynamic Graph Convolutional Networks for Crowd Flows Prediction
inferred← citeshttps://doi.org/10.3390/app13127271openalex-snapshot
Dynamic Graph Convolutional Crowd Flow Prediction Model Based on Residual Network Structure
inferred← citeshttps://doi.org/10.3390/math12111739openalex-snapshot
ARFGCN: Adaptive Receptive Field Graph Convolutional Network for Urban Crowd Flow Prediction
inferred← citeshttps://doi.org/10.70985/qnwmvn34openalex-snapshot
User Behavior Analysis and Security Strategy Optimization of College English Learning Platform Using Dynamic Graph Convolutional Network
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.