| ResLogit: A residual neural network logit model for data-driven choice modelling M Wong, B Farooq Transportation Research Part C: Emerging Technologies 126, 103050, 2021 | 42* | 2021 |
| Discriminative conditional restricted Boltzmann machine for discrete choice and latent variable modelling M Wong, B Farooq, GA Bilodeau Journal of choice modelling 29, 152-168, 2018 | 38 | 2018 |
| An investigation into machine learning approaches for forecasting spatio-temporal demand in ride-hailing service I Saadi, M Wong, B Farooq, J Teller, M Cools arXiv preprint arXiv:1703.02433, 2017 | 36 | 2017 |
| A bi-partite generative model framework for analyzing and simulating large scale multiple discrete-continuous travel behaviour data M Wong, B Farooq Transportation Research Part C: Emerging Technologies 110, 247-268, 2020 | 25 | 2020 |
| Latent behaviour modelling using discriminative restricted Boltzmann machines M Wong, B Farooq, GA Bilodeau 5th International Choice Modeling Conference, 1-18, 2017 | 6 | 2017 |
| Modelling latent travel behaviour characteristics with generative machine learning M Wong, B Farooq 2018 21st International Conference on Intelligent Transportation Systems …, 2018 | 5 | 2018 |
| Information processing constraints in travel behaviour modelling: A generative learning approach M Wong, B Farooq arXiv preprint arXiv:1907.07036, 2019 | 3 | 2019 |
| Next direction route choice model for cyclist using panel data M Wong, B Farooq, GA Bilodeau | 2 | 2016 |
| Battery swapping demand simulation for electric micromobility vehicles considering multi-source information interaction and behavior decision F Zhang, H Lyu, Y Ji, M Wong, C Kuai, J Fan Journal of Cleaner Production 414, 137525, 2023 | 1 | 2023 |
| Prompt Evolution for Generative AI: A Classifier-Guided Approach M Wong, YS Ong, A Gupta, KK Bali, C Chen 2023 IEEE Conference on Artificial Intelligence (CAI), 226-229, 2023 | 1 | 2023 |
| Latent Class model using discriminative restricted Boltzmann Machine M Wong, B Farooq, GA Bilodeau International Choice Modelling Conference 2017, 2017 | 1 | 2017 |
| Unimodal Ordinal Logit: A Logit Model with a Utility-Correction Term Capturing Correlations from Ordinal Responses M Wong, S Varotto, M Bierlaire Available at SSRN 4220600, 2022 | | 2022 |
| A Unimodal Ordered Logit model for ranked choices M Wong, JÁ Martín-Baos, M Bierlaire | | 2021 |
| Demystifying out-of-sample discrete choice prediction: What can we learn from machine learning? M Wong CMC Online Seminar Series 2020, 2020 | | 2020 |
| Distributed heterogeneous data learning approach for choice modelling using residual neural networks M Wong, B Farooq International Choice Modelling Conference 2019, 2019 | | 2019 |
| Generative modelling and machine learning methods for travel behaviour analysis M Wong Ryerson University, 2019 | | 2019 |
| A generalized Product of Experts model for non-linear utility specifications in travel behaviour models M Wong, B Farooq Transportation Research Board 98th Annual MeetingTransportation Research Board, 2019 | | 2019 |
| On the Use of Conditional Restricted Boltzmann Machine for Implicit Modeling of Latent Travel Behavior Characteristics M Wong, B Farooq, A Sobhani Transportation Research Board 97th Annual MeetingTransportation Research Board, 2018 | | 2018 |
| Group ID U11418 Affiliated authors Antonini, Gianluca B Atasoy, S Ataç, I Azaïez, MM Bender, M Bierlaire, S Binder, ... | | |
Bilal FarooqToronto Metropolitan UniversityVerified email at ryerson.ca
