Despite the rapid advancement of mobile applications, predicting app usa...
In traditional deep learning algorithms, one of the key assumptions is t...
Counterfactuals operationalised through algorithmic recourse have become...
Crowdsourced annotation is vital to both collecting labelled data to tra...
Knowledge graphs (KGs) are becoming essential resources for many downstr...
The Intensive Care Unit (ICU) is one of the most important parts of a
ho...
Predicting the risk of in-hospital mortality from electronic health reco...
Human movements in the workspace usually have non-negligible relations w...
Forecasting building energy usage is essential for promoting sustainabil...
A road network, in the context of traffic forecasting, is typically mode...
New roads are being constructed all the time. However, the capabilities ...
In the context of mobile sensing environments, various sensors on mobile...
Group fairness is achieved by equalising prediction distributions betwee...
Traffic forecasting is a critical task to extract values from cyber-phys...
Sparsity is a common issue in many trajectory datasets, including human
...
Detecting abrupt changes in data distribution is one of the most signifi...
Ordinary Differential Equations (ODE)-based models have become popular
f...
Predicting the health risks of patients using Electronic Health Records ...
This paper studies the time series forecasting problem from a whole new
...
In this paper, we propose a novel pipeline that leverages language found...
Digital Assistants (DAs) can support workers in the workplace and beyond...
Self-Supervised Learning (SSL) is a new paradigm for learning discrimina...
Building models for health prediction based on Electronic Health Records...
Recently, Self-Supervised Representation Learning (SSRL) has attracted m...
Disentangled representation learning offers useful properties such as
di...
Seating location in the classroom can affect student engagement, involve...
As a decisive part in the success of Mobility-as-a-Service (MaaS),
spati...
Existing human mobility forecasting models follow the standard design of...
Heterogeneity and irregularity of multi-source data sets present a
signi...
Human mobility prediction is a core functionality in many location-based...
App usage prediction is important for smartphone system optimization to
...
Multivariate time series (MTS) prediction plays a key role in many field...
Inferring human mental state (e.g., emotion, depression, engagement) wit...
Existing parking recommendation solutions mainly focus on finding and
su...
Managing individuals' attention and interruptibility is still a challeng...
To model and forecast flight delays accurately, it is crucial to harness...
The usage of smartphone-collected respiratory sound, trained with deep
l...
We conducted a field study at a K-12 private school in the suburbs of
Me...
We propose an uncertainty-aware service approach to provide drone-based
...
Change Point Detection techniques aim to capture changes in trends and
s...
Traffic flow prediction is a crucial task in enabling efficient intellig...
This paper investigates the Cyber-Physical behavior of users in a large
...
Generative Adversarial Networks (GANs) have shown remarkable success in ...
A well-crafted police patrol route design is vital in providing communit...
Due to the increasing nature of flexible work and the recent requirement...
We propose grid2vec, a novel approach for image representation learning
...
Network alignment is useful for multiple applications that require
incre...
Smartphones, wearables, and Internet of Things (IoT) devices produce a w...
Extracting informative and meaningful temporal segments from high-dimens...
In the opening months of 2020, COVID-19 changed the way for which people...