131 citations · 330 across the 19 of their papers we have counts for
19 papers
Message Passing Neural Networks for Traffic Forecasting
Arian Prabowo, Hao Xue, Wei Shao +2
A road network, in the context of traffic forecasting, is typically modeled as a graph where the nodes are sensors that measure traffic metrics (such as speed) at that location. Tr…
Traffic Forecasting on New Roads Using Spatial Contrastive Pre-Training (SCPT)
Arian Prabowo, Hao Xue, Wei Shao +2
New roads are being constructed all the time. However, the capabilities of previous deep forecasting models to generalize to new roads not seen in the training data (unseen roads)…
Because Every Sensor Is Unique, so Is Every Pair: Handling Dynamicity in Traffic Forecasting
Arian Prabowo, Wei Shao, Hao Xue +2
Traffic forecasting is a critical task to extract values from cyber-physical infrastructures, which is the backbone of smart transportation. However owing to external contexts, the…
Multiple-level Point Embedding for Solving Human Trajectory Imputation with Prediction
Kyle K. Qin, Yongli Ren, Wei Shao +3
Sparsity is a common issue in many trajectory datasets, including human mobility data. This issue frequently brings more difficulty to relevant learning tasks, such as trajectory i…
Integrated Convolutional and Recurrent Neural Networks for Health Risk Prediction using Patient Journey Data with Many Missing Values
Yuxi Liu, Shaowen Qin, Antonio Jimeno Yepes +3
Predicting the health risks of patients using Electronic Health Records (EHR) has attracted considerable attention in recent years, especially with the development of deep learning…
Compound Density Networks for Risk Prediction using Electronic Health Records
Yuxi Liu, Shaowen Qin, Zhenhao Zhang +1
Electronic Health Records (EHRs) exhibit a high amount of missing data due to variations of patient conditions and treatment needs. Imputation of missing values has been considered…
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…
Individual and Group-wise Classroom Seating Experience: Effects on Student Engagement in Different Courses
Nan Gao, Mohammad Saiedur Rahaman, Wei Shao +2
Seating location in the classroom can affect student engagement, attention and academic performance by providing better visibility, improved movement, and participation in discussi…
MoParkeR : Multi-objective Parking Recommendation
Mohammad Saiedur Rahaman, Wei Shao, Flora D. Salim +5
Existing parking recommendation solutions mainly focus on finding and suggesting parking spaces based on the unoccupied options only. However, there are other factors associated wi…
Predicting Flight Delay with Spatio-Temporal Trajectory Convolutional Network and Airport Situational Awareness Map
Wei Shao, Arian Prabowo, Sichen Zhao +2
To model and forecast flight delays accurately, it is crucial to harness various vehicle trajectory and contextual sensor data on airport tarmac areas. These heterogeneous sensor d…
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…
G-CREWE: Graph CompREssion With Embedding for Network Alignment
Kyle K. Qin, Flora D. Salim, Yongli Ren +3
Network alignment is useful for multiple applications that require increasingly large graphs to be processed. Existing research approaches this as an optimization problem or comput…
n-Gage: Predicting in-class Emotional, Behavioural and Cognitive Engagement in the Wild
Nan Gao, Wei Shao, Mohammad Saiedur Rahaman +1
The study of student engagement has attracted growing interests to address problems such as low academic performance, disaffection, and high dropout rates. Existing approaches to m…
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…
Transfer Learning for Thermal Comfort Prediction in Multiple Cities
Nan Gao, Wei Shao, Mohammad Saiedur Rahaman +3
HVAC (Heating, Ventilation and Air Conditioning) system is an important part of a building, which constitutes up to 40% of building energy usage. The main purpose of HVAC, maintain…
Flight Delay Prediction using Airport Situational Awareness Map
Wei Shao, Arian Prabowo, Sichen Zhao +6
The prediction of flight delays plays a significantly important role for airlines and travelers because flight delays cause not only tremendous economic loss but also potential sec…
COLTRANE: ConvolutiOnaL TRAjectory NEtwork for Deep Map Inference
Arian Prabowo, Piotr Koniusz, Wei Shao +1
The process of automatic generation of a road map from GPS trajectories, called map inference, remains a challenging task to perform on a geospatial data from a variety of domains…
Predicting Personality Traits from Physical Activity Intensity
Nan Gao, Wei Shao, Flora D Salim
Call and messaging logs from mobile devices have been used to predict human personality traits successfully in recent years. However, the widely available accelerometer data is not…
Approximating Optimisation Solutions for Travelling Officer Problem with Customised Deep Learning Network
Wei Shao, Flora D. Salim, Jeffrey Chan +2
Deep learning has been extended to a number of new domains with critical success, though some traditional orienteering problems such as the Travelling Salesman Problem (TSP) and it…