This paper presents a new perspective on time series forecasting. In existing time series
forecasting methods, the models take a sequence of numerical values as input and yield …

Trajectory computing is a pivotal domain encompassing trajectory data management and
mining, garnering widespread attention due to its crucial role in various practical …

Accurate human mobility prediction underpins many important applications across a variety
of domains, including epidemic modelling, transport planning, and emergency responses …

Mobility data captures the locations of moving objects such as humans, animals, and cars.
With the availability of GPS-equipped mobile devices and other inexpensive location …

In this paper, we propose a novel pipeline that leverages language foundation models for
temporal sequential pattern mining, such as for human mobility forecasting tasks. For …

Transformers have been an efficient alternative to recurrent neural networks in many
sequential learning tasks. When adapting transformers to modeling trajectories, we …

Trajectory prediction is an important task to support safe and intelligent behaviours in
autonomous systems. Many advanced approaches have been proposed over the years with …

Predicting the next visited location of an individual is a key problem in human mobility
analysis, as it is required for the personalization and optimization of sustainable transport …

As a decisive part in the success of Mobility-as-a-Service (MaaS), spatio-temporal predictive
modeling for crowd movements is a challenging task particularly considering scenarios …

Accurate activity location prediction is a crucial component of many mobility applications and
is particularly required to develop personalized, sustainable transportation systems. Despite …