33 citations · 63 across the 5 of their papers we have counts for
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econ.EM2019
ResLogit: A residual neural network logit model for data-driven choice modelling
Melvin Wong, Bilal Farooq
This paper presents a novel deep learning-based travel behaviour choice model.Our proposed Residual Logit (ResLogit) model formulation seamlessly integrates a Deep Neural Network (…
econ.EM2019★ 1 cited
Information processing constraints in travel behaviour modelling: A generative learning approach
Melvin Wong, Bilal Farooq
Travel decisions tend to exhibit sensitivity to uncertainty and information processing constraints. These behavioural conditions can be characterized by a generative learning proce…
stat.ML2019★ 33 cited
A bi-partite generative model framework for analyzing and simulating large scale multiple discrete-continuous travel behaviour data
Melvin Wong, Bilal Farooq
The emergence of data-driven demand analysis has led to the increased use of generative modelling to learn the probabilistic dependencies between random variables. Although their a…