Shenhao Wang

According to our database, Shenhao Wang authored at least 16 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

Fairness-enhancing deep learning for ride-hailing demand prediction.

Yunhan Zheng, Qingyi Wang, Dingyi Zhuang, Shenhao Wang, Jinhua Zhao

CoRR, 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

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

Qingyi Wang, Shenhao Wang, Dingyi Zhuang, Haris N. Koutsopoulos, Jinhua Zhao

CoRR, 2023

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, Shenhao Wang, Yulin Hu

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

2022

Alleviating Data Sparsity Problems in Estimated Time of Arrival via Auxiliary Metric Learning.

Yiwen Sun, Wenzheng Hu, Donghua Zhou, Baichuan Mo, Kun Fu, Zhengping Che, Zheng Wang, Shenhao Wang, Jinhua Zhao, Jieping Ye, Jian Tang, Changshui Zhang

IEEE Trans. Intell. Transp. Syst., 2022

End-to-end video compression for surveillance and conference videos.

Shenhao Wang, Yu Zhao, Han Gao, Mao Ye, Shuai Li

Multim. Tools Appl., 2022

Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks.

Dingyi Zhuang, Shenhao Wang, Haris N. Koutsopoulos, Jinhua Zhao

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

Equality of opportunity in travel behavior prediction with deep neural networks and discrete choice models.

Yunhan Zheng, Shenhao Wang, 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

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

Choice modelling in the age of machine learning.

Sander van Cranenburgh, Shenhao Wang, Akshay Vij, Francisco Pereira, Joan Walker

CoRR, 2021

2020

Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks.

Shenhao Wang, Baichuan Mo, Jinhua Zhao

CoRR, 2020

2019

Deep Neural Networks for Choice Analysis: Architectural Design with Alternative-Specific Utility Functions.

Shenhao Wang, Jinhua Zhao

CoRR, 2019

Multitask Learning Deep Neural Network to Combine Revealed and Stated Preference Data.

Shenhao Wang, Jinhua Zhao

CoRR, 2019

2018

Using Deep Neural Network to Analyze Travel Mode Choice With Interpretable Economic Information: An Empirical Example.

Shenhao Wang, Jinhua Zhao

CoRR, 2018