Using Deep Neural Network to Analyze Travel Mode Choice With Interpretable Economic Information: An Empirical Example. - Shenhao Wang; Jinhua Zhao (CoRR, 2018)

Multitask Learning Deep Neural Network to Combine Revealed and Stated Preference Data. - Shenhao Wang; Jinhua Zhao (CoRR, 2019)

Deep Neural Networks for Choice Analysis: Architectural Design with Alternative-Specific Utility Functions. - Shenhao Wang; Jinhua Zhao (CoRR, 2019)

Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks. - Shenhao Wang; Baichuan Mo; Jinhua Zhao (CoRR, 2020)

Choice modelling in the age of machine learning. - Sander van Cranenburgh; Shenhao Wang; Akshay Vij; Francisco Pereira 002; Joan Walker (CoRR, 2021)

Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark. - Shenhao Wang; Baichuan Mo; Stephane Hess; Jinhua Zhao (CoRR, 2021)

Estimating air quality co-benefits of energy transition using machine learning. - Da Zhang; Qingyi Wang; Shaojie Song; Simiao Chen; Mingwei Li; Lu Shen; Siqi Zheng; Bofeng Cai; Shenhao Wang (CoRR, 2021)

Equality of opportunity in travel behavior prediction with deep neural networks and discrete choice models. - Yunhan Zheng; Shenhao Wang; Jinhua Zhao (CoRR, 2021)

Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks. - Dingyi Zhuang; Shenhao Wang; Haris N. Koutsopoulos; Jinhua Zhao (KDD, 2022)

End-to-end video compression for surveillance and conference videos. - Shenhao Wang; Yu Zhao; Han Gao; Mao Ye 001; Shuai Li 005 (Multim. Tools Appl., 2022)

Alleviating Data Sparsity Problems in Estimated Time of Arrival via Auxiliary Metric Learning. - Yiwen Sun; Wenzheng Hu; Donghua Zhou; Baichuan Mo; Kun Fu 002; Zhengping Che; Zheng Wang 010; Shenhao Wang; Jinhua Zhao; Jieping Ye; Jian Tang 008; Changshui Zhang (IEEE Trans. Intell. Transp. Syst., 2022)

ST-GIN: An Uncertainty Quantification Approach in Traffic Data Imputation with Spatio-Temporal Graph Attention and Bidirectional Recurrent United Neural Networks. - Zepu Wang; Dingyi Zhuang; Yankai Li; Jinhua Zhao; Peng Sun 007; Shenhao Wang; Yulin Hu (ITSC, 2023)

Deep hybrid model with satellite imagery: how to combine demand modeling and computer vision for behavior analysis? - Qingyi Wang; Shenhao Wang; Yunhan Zheng; Hongzhou Lin; Xiaohu Zhang; Jinhua Zhao; Joan Walker (CoRR, 2023)

Fairness-enhancing deep learning for ride-hailing demand prediction. - Yunhan Zheng; Qingyi Wang; Dingyi Zhuang; Shenhao Wang; Jinhua Zhao (CoRR, 2023)

Spatiotemporal Graph Neural Networks with Uncertainty Quantification for Traffic Incident Risk Prediction. - Xiaowei Gao; Xinke Jiang; Dingyi Zhuang; Huanfa Chen; Shenhao Wang; James Haworth (CoRR, 2023)

SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks. - Dingyi Zhuang; Yuheng Bu; Guang Wang 001; Shenhao Wang; Jinhua Zhao (SIGSPATIAL/GIS, 2024)

Deep neural networks for choice analysis: Enhancing behavioral regularity with gradient regularization. - Siqi Feng; Rui Yao; Stephane Hess; Ricardo A. Daziano; Timothy Brathwaite; Joan Walker; Shenhao Wang (CoRR, 2024)

Advancing Transportation Mode Share Analysis with Built Environment: Deep Hybrid Models with Urban Road Network. - Dingyi Zhuang; Qingyi Wang; Yunhan Zheng; Xiaotong Guo; Shenhao Wang; Haris N. Koutsopoulos; Jinhua Zhao (CoRR, 2024)

Sparkle: Mastering Basic Spatial Capabilities in Vision Language Models Elicits Generalization to Composite Spatial Reasoning. - Yihong Tang; Ao Qu; Zhaokai Wang; Dingyi Zhuang; Zhaofeng Wu; Wei Ma; Shenhao Wang; Yunhan Zheng; Zhan Zhao; Jinhua Zhao (CoRR, 2024)

Uncertainty Quantification of Spatiotemporal Travel Demand With Probabilistic Graph Neural Networks. - Qingyi Wang; Shenhao Wang; Dingyi Zhuang; Haris N. Koutsopoulos; Jinhua Zhao (IEEE Trans. Intell. Transp. Syst., 2024)

Robust Transit Frequency Setting Problem With Demand Uncertainty. - Xiaotong Guo; Baichuan Mo; Haris N. Koutsopoulos; Shenhao Wang; Jinhua Zhao (IEEE Trans. Intell. Transp. Syst., 2024)

GETS: Ensemble Temperature Scaling for Calibration in Graph Neural Networks. - Dingyi Zhuang; Chonghe Jiang; Yunhan Zheng; Shenhao Wang; Jinhua Zhao (ICLR, 2025)

Mitigating Spatial Disparity in Urban Prediction Using Residual-Aware Spatiotemporal Graph Neural Networks: A Chicago Case Study. - Dingyi Zhuang; Hanyong Xu; Xiaotong Guo; Yunhan Zheng; Shenhao Wang; Jinhua Zhao (WWW (Companion Volume), 2025)

Virtual Nodes Improve Long-term Traffic Prediction. - Xiaoyang Cao; Dingyi Zhuang; Jinhua Zhao; Shenhao Wang (CoRR, 2025)

Analyzing sequential activity and travel decisions with interpretable deep inverse reinforcement learning. - Yuebing Liang; Shenhao Wang; Jiangbo Yu; Zhan Zhao; Jinhua Zhao; Sandy Pentland (CoRR, 2025)

Generative AI for Urban Planning: Synthesizing Satellite Imagery via Diffusion Models. - Qingyi Wang; Yuebing Liang; Yunhan Zheng; Kaiyuan Xu; Jinhua Zhao; Shenhao Wang (CoRR, 2025)

Generative AI for Urban Design: A Stepwise Approach Integrating Human Expertise with Multimodal Diffusion Models. - Mingyi He; Yuebing Liang; Shenhao Wang; Yunhan Zheng; Qingyi Wang; Dingyi Zhuang; Li Tian; Jinhua Zhao (CoRR, 2025)

Leveraging the Spatial Hierarchy: Coarse-to-fine Trajectory Generation via Cascaded Hybrid Diffusion. - Baoshen Guo; Zhiqing Hong; Junyi Li; Shenhao Wang; Jinhua Zhao (CoRR, 2025)

Graph neural networks for residential location choice: connection to classical logit models. - Zhanhong Cheng; Lingqian Hu; Yuheng Bu; Yuqi Zhou; Shenhao Wang (CoRR, 2025)

UQGNN: Uncertainty Quantification of Graph Neural Networks for Multivariate Spatiotemporal Prediction. - Dahai Yu; Dingyi Zhuang; Lin Jiang 007; Rongchao Xu; Xinyue Ye; Yuheng Bu; Shenhao Wang; Guang Wang 001 (CoRR, 2025)