Spatiotemporal Forecasting

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39 papers in the last four weeks, up 290% on the four weeks before. 0.4% of all new papers.

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Latest papers 279

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Beyond Time Series: Spatial Reasoning for Epidemic Forecasting via Multimodal Learning
Jun 20, 2026Diana Guadalupe Gomez, Chenwei Wu, Zhiyi Wang +2Epidemic Forecasting Spatiotemporal Reasoning
University of Michigan Ann Arbor, MI, USA
An Efficient and Effective Architecture for Large-Scale Traffic Prediction via Geometry-Adaptive Square Partitioning
Jun 19, 2026Yongfeng Su, Hongwen Li, Zijian Zhang +3Traffic Flow Estimation Spatiotemporal Forecasting
Zhejiang University, China · Southeast University, China · Aalborg University, Denmark
Structure-Aware Graph Multi-Task Learning for Dynamic Sparse OD Demand Prediction
Jun 19, 2026Ming Xu, Jiawei CaoIntelligent Transportation Systems Multi-Task Learning
Software College, Liaoning Technical University, Huludao, Liaoning 125100, China
Enhancing Graph Neural Networks Using Proximity Graphs for Dust Source Emission Forecasting
Jun 18, 2026Maryam Sanisales, Zahed Rahmati, Ali Darvishi Boloorani +1Graph Neural Networks Spatiotemporal Forecasting
Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran · Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran
Understanding Key Features of Time Series Foundation Models from Epidemic Forecasting
Jun 17, 2026Alireza Jafari, Judy Fox, Geoffrey C. Fox +2Epidemic Forecasting LLM-Based Time Series Forecasting
Department of Computer Science, School of Engineering and Applied Science, University of Virginia, Charlottesville, VA 22904 USA · School of Data Science, University of Virginia, Charlottesville, VA 22904 USA · Biocomplexity Institute and the Department of Computer Science, School of Engineering and Applied Science, University of Virginia, Charlottesville, VA 22904 USA +1
INDEQS: Informed Neural controlled Differential EQuationS
Jun 17, 2026Michael Detzel, Gabriel Nobis, Kristiyan Blagov +3Neural Controlled Differential Equations Spatiotemporal Forecasting
Fraunhofer Heinrich Hertz Institute · Technische Universität Berlin
Investigating Inductive Biases for Machine Learning Emulation of Sudden Stratospheric Warmings in Idealised Isca Simulations
Jun 17, 2026Oskar Bohn Lassen, Simon Driscoll, Stephen I. Thomson +2Neural Surrogate Modeling Climate Science
Department of Technology, Management, and Economics Technical University of Denmark · Department of Applied Mathematics and Theoretical Physics University of Cambridge · Department of Mathematics and Statistics University of Exeter
ASTEROID: A Spatiotemporal Information Transformer for Forecasting Multi-Step Time Series of Molecular Dynamics
Jun 16, 2026Kexin Wu, Luonan Chen, Renxiao WangSpatiotemporal Forecasting Molecular Dynamics Simulation
Department of Medicinal Chemistry, School of Pharmaceutical Sciences, Fudan University, 826 Zhangheng Road, Shanghai 201203, People's Republic of China · School of Mathematical Sciences and School of AI, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China
Towards Fast GNN Surrogates for CO2 Migration in Complex Geological Formations
Jun 15, 2026Rodrigo S. Luna, Thiago H. N. Coelho, Luiz S. L. Neto +8Graph Neural Networks PDE Surrogate Modeling
Systems and Computer Engineering and High Performance Computing Center, NACAD - COPPE, Federal University of Rio de Janeiro · Civil Engineering and High Performance Computing Center, NACAD - COPPE, Federal University of Rio de Janeiro · Mechanical Engineering and High Performance Computing Center, NACAD - COPPE, Federal University of Rio de Janeiro +1
When the Past Matters: FlashBack Memory for Precipitation Nowcasting
Jun 15, 2026Yuhao Du, Boxiao Huang, Chengrong Wu +1Memory-Augmented Neural Networks Precipitation Forecasting
College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China · Fuqua School of Business, Duke University, North Carolina 27705, USA · Department of Computer Science, University of Manchester, Manchester M139PL, UK
UrbanWell: Benchmarking Multimodal Large Language Models for Spatio-Temporal Urban Wellbeing Analytics
Jun 14, 2026Yanxin Xi, Xiang Su, Jie Feng +3Spatiotemporal Reasoning Multimodal Large Language Models
Department of Computer Science, University of Helsinki, Helsinki, Finland · Department of Computer Science, Department of Agricultural Sciences, University of Helsinki, Helsinki, Finland · Zhongguancun Academy, Beijing, China +2
Continuous Cross-Domain Traffic State Prediction via Memory-Augmented Graph Liquid Time-Constant Networks
Jun 14, 2026Jinrong Xiang, Ming XuCross-Domain Transfer Learning Spatiotemporal Forecasting
Software College, Liaoning Technical University, Huludao, Liaoning 125100, China
DYNA-PRUNER: Input-Adaptive Data-Model Co-Pruning for Efficient and Scalable Spatio-Temporal Media Prediction
Jun 13, 2026Fuyan Zhang, Yuqi Li, Qing Xu +2Efficient Neural Network Inference Spatiotemporal Forecasting
University of Edinburgh · The City College of New York, City University of New York · Institute of Computing Technology, Chinese Academy of Sciences +1
OmniPMNet: Bridging discrete and gridded PM10 forecasts via omni-query neural processes
Jun 12, 2026Shuangshuang He, Shuo WangAir Quality Prediction Spatiotemporal Forecasting
ColorfulClouds Technology Co., Ltd., 100875 Beijing, China. · School of Systems Science, Beijing Normal University, 100875 Beijing, China. · D-ITET, ETH Zurich, 8092 Zurich, Switzerland.
Nonlocal Bayesian Modeling of Continuous Spatio-Temporal Dynamics
Jun 12, 2026Jaeyeong Lee, Heeyoung KimIrregular Time-Series Modeling Bayesian Inference
Department of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
Can Machine Learning Forecast Rice Yields in Data-Constrained Settings? Satellite Climate Data, National Crop Statistics, and Lessons from Sierra Leone
Jun 11, 2026Ibrahim Denis FofanahTime Series Forecasting Spatiotemporal Forecasting
Seidenberg School of Computer Science & Information Systems, Pace University, New York, USA · RiseAfrica Foundation for STEM and Innovation, Sierra Leone, West Africa
MP3: Multi-Period Pattern Pre-training for Spatio-Temporal Forecasting
Jun 11, 2026Lilan Peng, Yandi Liu, Qingren Yao +2Spatiotemporal Forecasting Multiscale Time-Series Modeling
School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu 611756, China · Eindhoven University of Technology, Eindhoven 5612 AZ, Netherlands
Reliability of Probabilistic Emulation of Physical Systems
Jun 11, 2026Sam F. Greenbury, Radka Jersakova, Paolo Conti +4Surrogate Modeling Probabilistic Forecasting
The Alan Turing Institute · Autodesk Research · PhysicsX +3
PCA-Enhanced Adaptive NVAR Framework for High-Resolution Sea Surface Temperature Forecasting in the East Sea
Jun 10, 2026Sherkhon Azimov, Susana López-Moreno, Eric Dolores-Cuenca +2Neural Surrogate Modeling Reservoir Computing
Department of Mathematics, Pusan National University, Republic of Korea · Humanoid Olfactory Display Center, Pusan National University, Republic of Korea · Industrial Mathematics Center, Pusan National University, Republic of Korea +3
Neural-Parameterized Cellular Automata for Wildfire Spread
Jun 10, 2026Maksym Zhenirovskyy, Ion Matei, Rohit Vuppala +2Neural Cellular Automata Cellular Automata
Fujitsu Research of America, 4655 Great America Pkwy, Santa Clara, 95124, CA, USA
COGENT: Continuous Graph Emulators with Neural Ordinary Differential Equations for Long-Term Physical Forecasting
Jun 9, 2026Zesheng Liu, Maryam RahnemoonfarNeural Surrogate Modeling Long-Term Time Series Forecasting
Lehigh University · Bethlehem, Pennsylvania, USA
MoE Enhanced Federated Learning for Spatiotemporal Prediction
Jun 9, 2026Zhehao Dai, Xiao Han, Zhaolin Deng +4Intelligent Transportation Systems Mixture of Experts
Zhejiang University of Technology, Zhejiang Key Laboratory of Visual Information Intelligent Processing, Hangzhou · Jilin University, Jilin · City University of Hong Kong, Hong Kong SAR China
From Coarse to Fine: Managing Temporal Granularity in Spatio-Temporal Data for Fine-Grained Traffic Prediction
Jun 8, 2026Shuhao Li, Weidong Yang, Yue Cui +4Traffic Flow Estimation Spatiotemporal Forecasting
College of Computer Science and Artificial Intelligence, Fudan University, Shanghai 200082, China · Tongyi Lab, Alibaba Group, Cloud Valley, NO.1008 Dengcai Street, Xihu District, Hangzhou 310020, China · The Hong Kong University of Science and Technology, Hong Kong SAR 999077, China +1
Physics-Guided Dual Decoding and Spectral Supervision for Global 3D Hydrometeor Prediction
Jun 7, 2026Dandan Chen, Yaqiang WangPhysics-Informed ML Spatiotemporal Forecasting
KFTD: Koopman-Fourier Time-Differentiable Network for Continuous Ocean Spatiotemporal Forecasting
Jun 6, 2026Qinghui Chen, Zekai Zhang, Hailong Liu +2Koopman Operator Learning Physics-Informed ML
Shandong University School of Control Science and Engineering Jinan, China · Laoshan Laboratory Qingdao, China · Chinese Academy of sciences Institute of Atmospheric Physics Beijing, China +1
A Temporal Spatial Minimax Rate for Smoothly-Varying Distributions in Wasserstein Space
Jun 5, 2026Munsik KimMinimax Estimation Spatiotemporal Forecasting
Hierarchical Forecast Reconciliation for Urban Rail Transit Demand Prediction under Operational Disruptions
Jun 5, 2026Dang Viet Anh Nguyen, Alma Fazlagic, Kristine Pryds Loft +1Time Series Forecasting Spatiotemporal Forecasting
Department of Technology, Management, and Economics, Technical University of Denmark (DTU), 2800 Kongens Lyngby, Denmark
DSFNet: Learning Dual-Domain Spectral Operators for Multi-Modality Spatio-Temporal Forecasting in Urban Transportation Systems
Jun 5, 2026Yongchao Li, Yang Li, Zhuoxuan Li +4Intelligent Transportation Systems Time Series Forecasting
School of Transportation, Southeast University, Nanjing 211189, China · Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 211189, China · Department of Data Science, City University of Hong Kong, Hong Kong 999077, China +6
Vessel Traffic Flow Prediction on Sparse Data via Spatio-Temporal Graph Neural Networks with a Learnable Tweedie Head
Jun 5, 2026Kyeongjun Lee, Heeyoung KimSpatiotemporal Forecasting Spatiotemporal GNNs
Department of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
Learned Response-Field Inertia Operator for HEC-RAS 2D Water-Surface Elevation Prediction
Jun 4, 2026Edward Holmberg, Elias Ioup, Md Meftahul Ferdaus +2Neural Surrogate Modeling PDE Surrogate Modeling
Canizaro Livingston Gulf States Center for Environmental Informatics, Department of Computer Science, The University of New Orleans, New Orleans, LA 70148, USA · Center for Geospatial Sciences, Naval Research Laboratory, Mississippi, USA · Ocean Sciences Division, Naval Research Laboratory, Mississippi, USA

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Beyond Time Series: Spatial Reasoning for Epidemic Forecasting via Multimodal Learning

Diana Guadalupe Gomez, Chenwei Wu, Zhiyi Wang, Liyue Shen+1

University of Michigan Ann Arbor, MI, USA

Epidemic Forecasting Spatiotemporal Reasoning Probabilistic Forecasting Spatiotemporal Forecasting Multimodal Fusion

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Epidemic forecasting models typically rely on surveillance data reported over administrative regions, treating them as atomic units, thereby obscuring sub-regional spatial structure that shapes disease dynamics. We introduce a spatially structured multimodal epidemic forecasting setting that integrates region-level temporal surveillance data with spatially localized auxiliary signals that are misaligned in resolution and structure, reflecting realistic public health reporting constraints. Building on this formulation, we propose M-SPICE (Multimodal SPatIal Context for Epidemic Forecasting), a structure-aware spatiotemporal forecasting framework that performs joint reasoning over temporal disease dynamics and spatial context via attention-based multimodal fusion, allowing spatial signals to selectively condition temporal representations across forecast horizons. We evaluate our approach on real-world COVID-19, influenza, and influenza-like illness (ILI) forecasting tasks under realistic real-time evaluation protocols. Across all forecasting settings, our method consistently outperforms state-of-the-art multivariate time-series, multimodal, and epidemiological forecasting baselines while maintaining strong probabilistic forecasting performance. Finally, interpretability analyses reveal when, where, and how spatial signals are leveraged, highlighting settings in which purely temporal, region-aggregated models are most likely to fail.

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