{"total":59,"rows":[{"id":"2101.11174","title":"Graph Neural Network for Traffic Forecasting: A Survey","created":"2021-01-27","cited_by_count":261,"area":null},{"id":"2307.03759","title":"A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection","created":"2023-07-07","cited_by_count":145,"area":null},{"id":"2112.03558","title":"Graph Neural Controlled Differential Equations for Traffic Forecasting","created":"2021-12-07","cited_by_count":133,"area":null},{"id":"2402.11838","title":"UniST: A Prompt-Empowered Universal Model for Urban Spatio-Temporal Prediction","created":"2024-02-19","cited_by_count":87,"area":null},{"id":"2108.09091","title":"DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction","created":"2021-08-20","cited_by_count":73,"area":null},{"id":"2203.15737","title":"Towards Spatio-Temporal Aware Traffic Time Series Forecasting--Full Version","created":"2022-03-29","cited_by_count":59,"area":null},{"id":"2210.02040","title":"GT-GAN: General Purpose Time Series Synthesis with Generative Adversarial Networks","created":"2022-10-05","cited_by_count":44,"area":null},{"id":"2205.13947","title":"Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer","created":"2022-05-27","cited_by_count":43,"area":null},{"id":"2206.13816","title":"Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series Forecasting","created":"2022-06-28","cited_by_count":36,"area":null},{"id":"2402.19348","title":"Deep Learning for Cross-Domain Data Fusion in Urban Computing: Taxonomy, Advances, and Outlook","created":"2024-02-29","cited_by_count":33,"area":null},{"id":"2309.13363","title":"MLPST: MLP is All You Need for Spatio-Temporal Prediction","created":"2023-09-23","cited_by_count":22,"area":null},{"id":"2304.14343","title":"LibCity: A Unified Library Towards Efficient and Comprehensive Urban Spatial-Temporal Prediction","created":"2023-04-27","cited_by_count":20,"area":null},{"id":"2305.14826","title":"Building Transportation Foundation Model via Generative Graph Transformer","created":"2023-05-24","cited_by_count":19,"area":null},{"id":"2106.06064","title":"RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting","created":"2021-06-10","cited_by_count":16,"area":null},{"id":"2305.19591","title":"Traffic Prediction using Artificial Intelligence: Review of Recent Advances and Emerging Opportunities","created":"2023-05-31","cited_by_count":16,"area":null},{"id":"2206.02218","title":"Statistical Deep Learning for Spatial and Spatio-Temporal Data","created":"2022-06-05","cited_by_count":15,"area":null},{"id":"2303.10909","title":"Graph Neural Rough Differential Equations for Traffic Forecasting","created":"2023-03-20","cited_by_count":14,"area":null},{"id":"2306.06930","title":"Localised Adaptive Spatial-Temporal Graph Neural Network","created":"2023-06-12","cited_by_count":14,"area":null},{"id":"2309.12028","title":"Dynamic Hypergraph Structure Learning for Traffic Flow Forecasting","created":"2023-09-21","cited_by_count":14,"area":null},{"id":"2107.00946","title":"Online Metro Origin-Destination Prediction via Heterogeneous Information Aggregation","created":"2021-07-02","cited_by_count":12,"area":null},{"id":"2102.06027","title":"STUaNet: Understanding uncertainty in spatiotemporal collective human mobility","created":"2021-02-09","cited_by_count":11,"area":null},{"id":"2110.12763","title":"SSMF: Shifting Seasonal Matrix Factorization","created":"2021-10-25","cited_by_count":11,"area":null},{"id":"2208.03063","title":"Enhancing the Robustness via Adversarial Learning and Joint Spatial-Temporal Embeddings in Traffic Forecasting","created":"2022-08-05","cited_by_count":11,"area":null},{"id":"2407.09096","title":"STD-PLM: Understanding Both Spatial and Temporal Properties of Spatial-Temporal Data with PLM","created":"2024-07-12","cited_by_count":10,"area":null},{"id":"2410.22377","title":"A Systematic Literature Review of Spatio-Temporal Graph Neural Network Models for Time Series Forecasting and Classification","created":"2024-10-29","cited_by_count":9,"area":null},{"id":"2305.06587","title":"Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting","created":"2023-05-11","cited_by_count":8,"area":null},{"id":"2402.11773","title":"Dynamic Multi-Network Mining of Tensor Time Series","created":"2024-02-19","cited_by_count":8,"area":null},{"id":"2312.16403","title":"Learning Time-aware Graph Structures for Spatially Correlated Time Series Forecasting","created":"2023-12-27","cited_by_count":7,"area":null},{"id":"2104.10644","title":"A Comparative Study of Using Spatial-Temporal Graph Convolutional Networks for Predicting Availability in Bike Sharing Schemes","created":"2021-04-21","cited_by_count":6,"area":null},{"id":"2104.09369","title":"Adversarial Diffusion Attacks on Graph-based Traffic Prediction Models","created":"2021-04-19","cited_by_count":5,"area":null},{"id":"2105.05504","title":"An Empirical Experiment on Deep Learning Models for Predicting Traffic Data","created":"2021-05-12","cited_by_count":4,"area":null},{"id":"2402.09373","title":"Loss Shaping Constraints for Long-Term Time Series Forecasting","created":"2024-02-14","cited_by_count":4,"area":null},{"id":"2404.15734","title":"ODMixer: Fine-grained Spatial-temporal MLP for Metro Origin-Destination Prediction","created":"2024-04-24","cited_by_count":3,"area":null},{"id":"2408.10822","title":"Navigating Spatio-Temporal Heterogeneity: A Graph Transformer Approach for Traffic Forecasting","created":"2024-08-20","cited_by_count":3,"area":null},{"id":"2108.08170","title":"DeepExpress: Heterogeneous and Coupled Sequence Modeling for Express Delivery Prediction","created":"2021-08-18","cited_by_count":2,"area":null},{"id":"2201.05760","title":"Network Level Spatial Temporal Traffic State Forecasting with Hierarchical-Attention-LSTM (HierAttnLSTM)","created":"2022-01-15","cited_by_count":2,"area":null},{"id":"2203.02954","title":"On the importance of stationarity, strong baselines and benchmarks in transport prediction problems","created":"2022-03-06","cited_by_count":2,"area":null},{"id":"2301.11742","title":"Graph-Free Learning in Graph-Structured Data: A More Efficient and Accurate Spatiotemporal Learning Perspective","created":"2023-01-27","cited_by_count":2,"area":null},{"id":"2308.12899","title":"Unified Data Management and Comprehensive Performance Evaluation for Urban Spatial-Temporal Prediction [Experiment, Analysis & Benchmark]","created":"2023-08-24","cited_by_count":2,"area":null},{"id":"2406.08287","title":"Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks","created":"2024-06-12","cited_by_count":2,"area":null},{"id":"2410.14727","title":"Leveraging Intra-Period and Inter-Period Features for Enhanced Passenger Flow Prediction of Subway Stations","created":"2024-10-16","cited_by_count":2,"area":null},{"id":"2501.04239","title":"Dynamic Localisation of Spatial-Temporal Graph Neural Network","created":"2025-01-08","cited_by_count":2,"area":null},{"id":"2108.05940","title":"ST-PCNN: Spatio-Temporal Physics-Coupled Neural Networks for Dynamics Forecasting","created":"2021-08-12","cited_by_count":1,"area":null},{"id":"2110.02271","title":"Networked Time Series Prediction with Incomplete Data via Generative Adversarial Network","created":"2021-10-05","cited_by_count":1,"area":null},{"id":"2208.08878","title":"Towards Learning in Grey Spatiotemporal Systems: A Prophet to Non-consecutive Spatiotemporal Dynamics","created":"2022-08-17","cited_by_count":1,"area":null},{"id":"2308.06129","title":"Uncertainty Quantification for Image-based Traffic Prediction across Cities","created":"2023-08-11","cited_by_count":1,"area":null},{"id":"2410.15589","title":"SSMT: Few-Shot Traffic Forecasting with Single Source Meta-Transfer","created":"2024-10-21","cited_by_count":1,"area":null},{"id":"2602.21757","title":"Learning from Yesterday's Error: An Efficient Online Learning Method for Traffic Demand Prediction","created":"2026-02-25","cited_by_count":1,"area":null},{"id":"2107.01528","title":"Incorporating Reachability Knowledge into a Multi-Spatial Graph Convolution Based Seq2Seq Model for Traffic Forecasting","created":"2021-07-04","cited_by_count":0,"area":null},{"id":"2206.04053","title":"Unsupervised Knowledge Adaptation for Passenger Demand Forecasting","created":"2022-06-08","cited_by_count":0,"area":null},{"id":"2206.10160","title":"Predicting Parking Lot Availability by Graph-to-Sequence Model: A Case Study with SmartSantander","created":"2022-06-21","cited_by_count":0,"area":null},{"id":"2306.01282","title":"Recent Advances in Graph-based Machine Learning for Applications in Smart Urban Transportation Systems","created":"2023-06-02","cited_by_count":0,"area":null},{"id":"2401.13096","title":"Probabilistic Demand Forecasting with Graph Neural Networks","created":"2024-01-23","cited_by_count":0,"area":null},{"id":"2408.12409","title":"Multi-Source Knowledge-Based Hybrid Neural Framework for Time Series Representation Learning","created":"2024-08-22","cited_by_count":0,"area":null},{"id":"2408.12634","title":"Joint Hypergraph Rewiring and Memory-Augmented Forecasting Techniques in Digital Twin Technology","created":"2024-08-22","cited_by_count":0,"area":null},{"id":"2408.14387","title":"Reprogramming Foundational Large Language Models(LLMs) for Enterprise Adoption for Spatio-Temporal Forecasting Applications: Unveiling a New Era in Copilot-Guided Cross-Modal Time Series Representation Learning","created":"2024-08-26","cited_by_count":0,"area":null},{"id":"2412.17524","title":"STAHGNet: Modeling Hybrid-grained Heterogenous Dependency Efficiently for Traffic Prediction","created":"2024-12-23","cited_by_count":0,"area":null},{"id":"2607.24365","title":"MobiWave: Dispatch-Oriented Graph Wavelets and Drift-Guided Selective Optimization for Autonomous Fleet Rebalancing","created":"2026-07-27","cited_by_count":0,"area":null},{"id":"2609.31667","title":"Beyond the Graph: An Adaptive Meta-Learner Fuses Explainability, Weather, and Dynamics for Robust Bus ETA Prediction","created":"2026-09-14","cited_by_count":0,"area":null}],"next_cursor":null}