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Special Issue on Machine Learning Methods for Urban Passenger Mobility
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Special Issue on Machine Learning Methods for Urban Passenger Mobility
Pages:iii–vi
Published Online:July 25, 2025
Probabilistic Traffic Forecasting with Dynamic Regression
Pages:689–707
Published Online:April 8, 2025
Scalable Dynamic Mixture Model with Full Covariance for Probabilistic Traffic Forecasting
Pages:708–720
Published Online:March 14, 2025
Estimating Erratic Measurement Errors in Network-Wide Traffic Flow via Virtual Balance Sensors
Pages:721–742
Published Online:February 24, 2025
Using Multiple Biased Data Sets to Recover Missing Trips with a Behaviorally Informed Model
Pages:743–762
Published Online:May 16, 2025
Simultaneous Multimodal Demand Imputation and Forecasting via Graph-Guided Generative and Adversarial Network
Pages:763–781
Published Online:May 13, 2025
diffIRM: A Diffusion-Augmented Invariant Risk Minimization Framework for Spatiotemporal Prediction over Graphs
Pages:782–801
Published Online:April 8, 2025
Modeling Metro Passenger Routing Choices with a Fully Differentiable End-to-End Simulation-Based Optimization (SBO) Approach
Pages:802–822
Published Online:February 7, 2025
Toward Human-Like Trajectory Prediction for Autonomous Driving: A Behavior-Centric Approach
Pages:823–852
Published Online:May 7, 2025
End-to-End Learning of User Equilibrium: Expressivity, Generalization, and Optimization
Pages:853–882
Published Online:March 13, 2025
