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cs.LG2021
Multi-task Recurrent Neural Networks to Simultaneously Infer Mode and Purpose in GPS Trajectories
Ali Yazdizadeh, Arash Kalatian, Zachary Patterson +1
Multi-task learning is assumed as a powerful inference method, specifically, where there is a considerable correlation between multiple tasks, predicting them in an unique framewor…
cs.LG2019
Ensemble Convolutional Neural Networks for Mode Inference in Smartphone Travel Survey
Ali Yazdizadeh, Zachary Patterson, Bilal Farooq
We develop ensemble Convolutional Neural Networks (CNNs) to classify the transportation mode of trip data collected as part of a large-scale smartphone travel survey in Montreal, C…
cs.LG2019
Semi-supervised GANs to Infer Travel Modes in GPS Trajectories
Ali Yazdizadeh, Zachary Patterson, Bilal Farooq
Semi-supervised Generative Adversarial Networks (GANs) are developed in the context of travel mode inference with uni-dimensional smartphone trajectory data. We use data from a lar…