Spatiotemporal GNNs

GNN: Graph Neural Network

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Overview

Spatiotemporal graph neural networks represent entities such as traffic sensors, body joints, or mesh elements as nodes, and use their connections to model how information changes over time. Common approaches combine graph convolutions or attention with recurrent networks, temporal convolutions, Transformers, or continuous-time models; some also learn changing graph structure or incorporate physical constraints. They are used for traffic forecasting, human-motion prediction, environmental modeling, and simulation, with evaluation ranging from traffic datasets such as METR-LA and PEMS to motion benchmarks such as Human3.6M. A central challenge is balancing accuracy and long-horizon stability with computational cost, while ensuring models generalize across regions, changing conditions, and irregular or sparse observations.

Latest papers

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148 papers15 papers in the last four weeks, level with the four weeks before. 0.1% of all new papers.

  1. How Much Graph Is Too Much? Graph Construction and Exposure in Spatio-Temporal Forecasting

    Oct 25, 2026Saj Maru, Qiyu Han, Krishna MamidalaSpatiotemporal GNNsGraph Construction

  2. GraphCast-Mamba: Learning Non-Markovian Corrections for Weather Forecasting

    Oct 20, 2026Ilya Vilkoviskiy, Liang-Hong Mo, Suozhi Huang +1Weather ForecastingTime Series Forecasting

    Department of Physics, Princeton University, Princeton, NJ 08544, USA · Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ 08544, USA · École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland +2

  3. Cross-Visibility-Gap Identity Persistence for 4D Scene Graphs

    Oct 20, 2026Jiahui Hu, Li Gao, Yu Liu +14D Scene UnderstandingMulti-Object Tracking

    Department of Computer Science, The University of Hong Kong · Chongqing University · Department of Computing, The Hong Kong Polytechnic University

  4. STC-MGNet: Spatial-Temporal-Channel Attention-Enhanced Multimodal Graph Network for Pedestrian Intention Prediction

    Oct 16, 2026Yuanzhe Li, Meng WangPedestrian Intention PredictionSpatiotemporal GNNs

    Chair of Automotive Engineering, Technische Universität Berlin, Berlin, Germany

  5. Towards a GraphNARX model for structural dynamics

    Oct 16, 2026George Tsialiamanis, Keith WordenNonlinear System IdentificationTime Series Modeling

    Dynamics Research Group, School of Mechanical, Aerospace, and Civil Engineering, University of Sheffield, Sheffield, Mappin St, Sheffield, United Kingdom

  6. Network-Wide Freeway Speed Nowcasting and Forecasting from Sparse Fixed Sensors with a Probe-Supervised Graph Convolutional Recurrent Network

    Oct 15, 2026Ran Tu, Zihao Li, Arash MirzaeiTraffic ForecastingTraffic Flow Estimation

    North Central Texas Council of Governments, Arlington, TX 76011, USA

  7. Learning to Forecast on Multiple Spatiotemporal Hierarchies

    Oct 15, 2026Valentina Moretti, Cesare Alippi, Andrea CiniTime Series ForecastingSpatiotemporal Forecasting

    IDSIA USI-SUPSI, Universit`a della Svizzera italiana · Politecnico di Milano · EPFL

  8. Learning and Forecasting Multiscale Spatiotemporal Epidemic Dynamics with Lagrangian-Eulerian Graph Neural ODEs

    Oct 15, 2026Jinyi Duan, Qian Li, Biao TangEpidemic ForecastingSpatial Epidemic Modeling

    School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, 710049, People’s Republic of China . · School of Mathematics and Statistics, Xi’an University of Technology, Xi’an, 710054, People’s Republic of China . · Center for Intersection of Mathematics and Life Sciences, Xi’an Jiaotong University, Xi’an, 710049, People’s Republic of China .

  9. FireGraphNet: Sub-daily wildfire spread prediction with directed graph neural networks

    Oct 13, 2026Aiyshwariya Paulvannan Kanmani, Miguel Esparza, Ali MostafaviWildfire ForecastingSpatiotemporal GNNs

    Urban Resilience.AI Lab, Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, TX 77840, United States of America

  10. From Rainfall to Road-Network Functionality: Transferable Graph Forecasting for Flood-Disrupted Transportation Networks

    Oct 10, 2026Junyan Wang, Naiyu WangSpatiotemporal ForecastingSpatiotemporal GNNs

    College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China

  11. Robot-WATCHDOG : failure detection through object-centric graph representation

    Oct 9, 2026Quentin Rolland, Fabrice Mayran de Chamisso, Jean-Baptiste MouretRobot Failure DetectionRobotic Anomaly Detection

    Universit´e Paris-Saclay, CEA, List, F-91120, Palaiseau, France · Inria, CNRS, Universit´e de Lorraine, LORIA, F-54000 Nancy, France · Bleu Robotics, Paris, France

  12. Textual Environmental Context and Spatial Graphs for LLM-Based Regional SST Forecasting

    Oct 6, 2026Xiong Li, Xiaowei Zhou, Yanwei Yu +2Spatiotemporal ForecastingLLM-Based Time Series Forecasting

    Ocean University of China, Qingdao, China

  13. LLM-enhanced spatio-temporal learning for grid-level docked bike sharing demand prediction

    Oct 2, 2026Xuxilu Zhang, Francesc SorigueraSpatiotemporal ForecastingTime Series Forecasting

    BIT – Universitat Polit`ecnica de Catalunya – Barcelona Tech (UPC), Jordi Girona 1–3, Building B1, Office 111, Barcelona 08034, Spain.

  14. Physics-Refined Spatiotemporal Forecasting on Open-Boundary Hydrologic Graphs

    Oct 1, 2026Haoyang Jiang, Zhengui Wang, Shenghan Gao +3Spatiotemporal ForecastingPhysics-Informed GNNs

    William & Mary, Williamsburg, VA, USA · Virginia Institute of Marine Science, William & Mary, Gloucester Point, VA, USA · Florida Atlantic University, Boca Raton, FL, USA

  15. FAST-Brain: A Flow-Aligned Spatio-Temporal Surrogate Brain Model

    Sep 28, 2026Shucheng Liu, Changchun Shi, Kai Zhang +1Neural Surrogate ModelingFunctional Connectivity

    University of North Carolina at Chapel Hill · London School of Economics and Political Science

  16. Skeletons in Flow: Graph Structured Flow Matching for Human Motion Prediction

    Sep 26, 2026Yixuan Wang, Brandon C. Fallin, Warren E. DixonHuman Motion PredictionFlow Matching

    Department of Mechanical and Aerospace Engineering University of Florida · Department of Engineering Virginia Tech

  17. Learning Local Heterogeneity and Cross-Region Context for Large-Scale Traffic Forecasting

    Sep 23, 2026Qi Feng, Zidong Wang, Bo Li +4Intelligent Transportation SystemsTraffic Forecasting

    School of Electronic and Information, Northwestern Polytechnical University, Xi’an 710129, China · Department of Computer Science, City University of Hong Kong, Hong Kong SAR, and also with Shenzhen Research Institute, City University of Hong Kong, China · School of Electronic Information (School of Artificial Intelligence), Northwest University, Xi’an, China

  18. SambaGraph: Action-Reaction Spatio-Temporal Graphs for Soccer Tactical Response Modeling

    Sep 22, 2026Abel A. Reyes-Angulo, Henry O. Velesaca, Steven AraujoSports Video AnalysisSoccer Analytics

    Michigan Technological University, Houghton, MI, USA · SambaSports AI, Guayaquil, Ecuador · ESPOL Polytechnic University, Guayaquil, Ecuador +1

  19. Multi-Term Fourier Graph Neural Network with Sample Relationship Learning for Enhanced Remaining Useful Life Prediction

    Sep 21, 2026Ya Song, Laurens Bliek, Yaoxin Wu +1Graph Neural NetworksRUL Estimation

    Information Systems, Department of Industrial Engineering & Innovation Sciences, Eindhoven University of Technology, Eindhoven, The Netherlands

  20. GraphToolbox: A Configurable Python Framework for Graph Neural Network Forecasting

    Sep 21, 2026Eloi Campagne, Yvenn Amara-Ouali, Yannig Goude +1Time Series ForecastingElectricity Load Forecasting

    CB · LMO, CELESTE · EDF R\&D +1

  21. TWIG: A Time-Causal Wavelet Operator for Autoregressive Forecasting on Irregular Graphs

    Sep 18, 2026Subashree Venkatasubramanian, David A. Barajas-Solano, Chuyang Liu +2Neural Surrogate ModelingSpatiotemporal GNNs

    Lawrence Berkeley National Laboratory, Berkeley, CA, USA · Stanford University, Stanford, CA, USA · Pacific Northwest National Laboratory, Richland, WA, USA

  22. FedeRICo: Federated Region-Influenced Coupling for Traffic Flow Prediction

    Sep 17, 2026Fermin Orozco, Man Luo, Johan WahlströmFederated Graph LearningSpatiotemporal Forecasting

    University of Exeter Exeter, United Kingdom

  23. A 25-μμs/inf Event-driven Graph Neural Network Processor with Spatiotemporal Caching and Spline Convolution for Ultra-low-latency AI at the Edge

    Sep 14, 2026Adrian Kneip, Martin Lefebvre, Daniel Gehrig +4Event-Based VisionAI Accelerator Inference

    Delft University of Technology (TU Delft), 2628 CD Delft, The Netherlands · KU Leuven, 3000 Leuven, Belgium · University of Zürich (UZH), 8050 Zürich, Switzerland +1

  24. STHMoE: Hypergraph-Enhanced Heterogeneous Dependency Coordination for LLM-Based Urban Traffic Data Forecasting

    Sep 14, 2026Jiawen Chen, Qi Shao, Yongjian Chang +3Traffic Flow EstimationLLM-Based Time Series Forecasting

    School of Mathematics, Southeast University, Nanjing 210096, China · School of Cyber Science and Engineering, Southeast University, Nanjing 210096, China · Jiangsu Province Center for Applied Mathematical Sciences, Nanjing 210096, China

  25. Single-Stream Multi-Feature Fusion with Temporal Robustness for Gait Emotion Recognition

    Sep 10, 2026Shirong Lyu, Silu Quan, Yixuan Ding +1Gait RecognitionInvariant Representation Learning

    College of Computer and Information Science, Southwest University, Chongqing, China · College of Physical Science and Technology, Southwest University, Chongqing, China · Wisesoft Inc., Chengdu, China

  26. A Dynamic Fusion Large Language Model for Traffic Flow Prediction

    Sep 10, 2026Xue Qiu, Jianli XiaoIntelligent Transportation SystemsTraffic Flow Estimation

    School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China

  27. When Does Advection-Aware Graph Nowcasting Help? A Controlled Study of Distributed Solar Ramp Forecasting with a Self-Supervised Cloud-Motion Estimator

    Sep 8, 2026Phillip JiangSolar Power ForecastingSolar Irradiance Forecasting

    Appsofa LLC

  28. TD-STGT: A Spatio-Temporal Graph Transformer for Mobile Traffic Demand Forecasting

    Sep 6, 2026Mohamad Alkadamani, Halim YanikomerogluTraffic ForecastingSpatiotemporal Forecasting

    Communications Research Centre Canada, Ottawa, ON, Canada · Department of Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada

  29. Predicting Spatiotemporal Mobile Sensing-Based PM2.5 Concentrations Using Low-Rank Adapted Spatially Attentive Graph Neural Network

    Sep 4, 2026Om Chiddarwar, Priyanka Mandal, Praveen Kumar Chandaliya +1Graph Attention NetworksAir Quality Prediction

    IIITDM Kurnool, Kurnool, Andhra Pradesh 518002, India · Sardar Vallabhbhai National Institute of Technology Surat, Gujarat 394210, India

  30. TRACE: A spatiotemporal contact memory graph network simulator for granular dynamics

    Sep 2, 2026Changjian Zhou, Negin Yousefpour, Jie Qi +3Physics-Based SimulationSpatiotemporal GNNs

    Faculty of Engineering and IT, The University of Melbourne · School of Computing, National University of Singapore · Norwegian Geotechnical Institute