33 citations · 63 across the 5 of their papers we have counts for
5 papers
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 (…
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…
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…
Modelling Latent Travel Behaviour Characteristics with Generative Machine Learning
Melvin Wong, Bilal Farooq
In this paper, we implement an information-theoretic approach to travel behaviour analysis by introducing a generative modelling framework to identify informative latent characteri…
An investigation into machine learning approaches for forecasting spatio-temporal demand in ride-hailing service
Ismaïl Saadi, Melvin Wong, Bilal Farooq +2
In this paper, we present machine learning approaches for characterizing and forecasting the short-term demand for on-demand ride-hailing services. We propose the spatio-temporal e…