With the rapid development of the Intelligent Transportation System (ITS...
Wave Function Collapse (WFC) is a widely used tile-based algorithm in
pr...
Epidemic prediction is a fundamental task for epidemic control and
preve...
Tensor time series (TTS) data, a generalization of one-dimensional time
...
In recent years, attention mechanisms have demonstrated significant pote...
Multivariate time-series (MTS) forecasting is a paramount and fundamenta...
Conventional reinforcement learning (RL) needs an environment to collect...
Travel time estimation from GPS trips is of great importance to order
du...
Spatio-temporal modeling as a canonical task of multivariate time series...
Spatial-temporal (ST) graph modeling, such as traffic speed forecasting ...
Traffic forecasting as a canonical task of multivariate time series
fore...
Estimating the travel time of a path is an essential topic for intellige...
Due to the rapid development of Internet of Things (IoT) technologies, m...
In recent years, due to the wider WiFi coverage and the popularization o...
In recent years, deep learning approaches have been proved good performa...
Consensus protocols are widely used in building reliable distributed sof...
As a decisive part in the success of Mobility-as-a-Service (MaaS),
spati...
Deep neural networks (DNNs) have achieved extraordinary performance in
s...
Travel mode detection has been a hot topic in the field of GPS
trajector...
Multi-variate time series (MTS) data is a ubiquitous class of data
abstr...
Nowadays, with the rapid development of IoT (Internet of Things) and CPS...
Human mobility similarity comparison plays a critical role in mobility
e...
Life pattern clustering is essential for abstracting the groups'
charact...
Data-driven epidemic simulation helps better policymaking. Compared with...
The coronavirus disease 2019 (COVID-19) outbreak has swept more than 180...
With the continued digitalization of societal processes, we are seeing a...
Nowadays, massive urban human mobility data are being generated from mob...
In this study, we formulate the concept of "mining maximal-size frequent...