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Uncertainty Quantification of Spatiotemporal Travel Demand with Probabilistic Graph Neural Networks.

, , , , and . CoRR, (2023)

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Choice modelling in the age of machine learning., , , , and . CoRR, (2021)Uncertainty Quantification of Spatiotemporal Travel Demand with Probabilistic Graph Neural Networks., , , , and . CoRR, (2023)Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark., , , and . CoRR, (2021)Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks., , and . CoRR, (2020)Advancing Transportation Mode Share Analysis with Built Environment: Deep Hybrid Models with Urban Road Network., , , , , , and . CoRR, (2024)Deep Neural Networks for Choice Analysis: Architectural Design with Alternative-Specific Utility Functions., and . CoRR, (2019)Deep hybrid model with satellite imagery: how to combine demand modeling and computer vision for behavior analysis?, , , , , , and . CoRR, (2023)Fairness-enhancing deep learning for ride-hailing demand prediction., , , , and . CoRR, (2023)Alleviating Data Sparsity Problems in Estimated Time of Arrival via Auxiliary Metric Learning., , , , , , , , , and 2 other author(s). IEEE Trans. Intell. Transp. Syst., 23 (12): 23231-23243 (2022)Deep neural networks for choice analysis: Enhancing behavioral regularity with gradient regularization., , , , , , and . CoRR, (2024)