8 citations · 14 across the 4 of their papers we have counts for
4 papers
Deep Neural Networks for Choice Analysis: Architectural Design with Alternative-Specific Utility Functions
Shenhao Wang, Baichuan Mo, Jinhua Zhao
Whereas deep neural network (DNN) is increasingly applied to choice analysis, it is challenging to reconcile domain-specific behavioral knowledge with generic-purpose DNN, to impro…
Multitask Learning Deep Neural Networks to Combine Revealed and Stated Preference Data
Shenhao Wang, Qingyi Wang, Jinhua Zhao
It is an enduring question how to combine revealed preference (RP) and stated preference (SP) data to analyze travel behavior. This study presents a framework of multitask learning…
Deep Neural Networks for Choice Analysis: Extracting Complete Economic Information for Interpretation
Shenhao Wang, Qingyi Wang, Jinhua Zhao
While deep neural networks (DNNs) have been increasingly applied to choice analysis showing high predictive power, it is unclear to what extent researchers can interpret economic i…
Deep Neural Networks for Choice Analysis: A Statistical Learning Theory Perspective
Shenhao Wang, Qingyi Wang, Nate Bailey +1
While researchers increasingly use deep neural networks (DNN) to analyze individual choices, overfitting and interpretability issues remain as obstacles in theory and practice. By…