4 papers · 1 filter
FairDRL-ST: Disentangled Representation Learning for Fair Spatio-Temporal Mobility Prediction
Sichen Zhao, Wei Shao, Jeffrey Chan +2
As deep spatio-temporal neural networks are increasingly utilised in urban computing contexts, the deployment of such methods can have a direct impact on users of critical urban in…
Measuring disentangled generative spatio-temporal representation
Sichen Zhao, Wei Shao, Jeffrey Chan +1
Disentangled representation learning offers useful properties such as dimension reduction and interpretability, which are essential to modern deep learning approaches. Although dee…
Generative Adversarial Networks for Spatio-temporal Data: A Survey
Nan Gao, Hao Xue, Wei Shao +5
Generative Adversarial Networks (GANs) have shown remarkable success in producing realistic-looking images in the computer vision area. Recently, GAN-based techniques are shown to…
FADACS: A Few-shot Adversarial Domain Adaptation Architecture for Context-Aware Parking Availability Sensing
Wei Shao, Sichen Zhao, Zhen Zhang +4
Existing research on parking availability sensing mainly relies on extensive contextual and historical information. In practice, the availability of such information is a challenge…