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Multitask Learning Deep Neural Networks to Combine Revealed and Stated Preference Data
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Multitask Learning Deep Neural Networks to Combine Revealed and Stated Preference Data

Shenhao Wang
Qingyi Wang
Jinhuan Zhao
ArXiv (abs)PDFHTML

Papers citing "Multitask Learning Deep Neural Networks to Combine Revealed and Stated Preference Data"

5 / 5 papers shown
Title
Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark
Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark
Shenhao Wang
Baichuan Mo
Stephane Hess
Jinhuan Zhao
Jinhua Zhao
119
6
0
01 Feb 2021
Gaussian Process Latent Class Choice Models
Gaussian Process Latent Class Choice Models
G. Sfeir
Filipe Rodrigues
Maya Abou-Zeid
GP
55
12
0
28 Jan 2021
Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks
Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks
Shenhao Wang
Baichuan Mo
Jinhuan Zhao
AI4CE
50
36
0
22 Oct 2020
Semi-nonparametric Latent Class Choice Model with a Flexible Class Membership Component: A Mixture Model Approach
Semi-nonparametric Latent Class Choice Model with a Flexible Class Membership Component: A Mixture Model Approach
G. Sfeir
Maya Abou-Zeid
Filipe Rodrigues
Francisco Câmara Pereira
I. Kaysi
32
16
0
06 Jul 2020
A Neural-embedded Choice Model: TasteNet-MNL Modeling Taste Heterogeneity with Flexibility and Interpretability
A Neural-embedded Choice Model: TasteNet-MNL Modeling Taste Heterogeneity with Flexibility and Interpretability
Yafei Han
F. Pereira
M. Ben-Akiva
C. Zegras
84
47
0
03 Feb 2020

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