10 citations · 12 across the 5 of their papers we have counts for
7 papers
FlexiReg: Flexible Urban Region Representation Learning
Fengze Sun, Yanchuan Chang, Egemen Tanin +2
The increasing availability of urban data offers new opportunities for learning region representations, which can be used as input to machine learning models for downstream tasks s…
TSMini: A Simple Yet Highly Effective Trajectory Similarity Learning Model
Yanchuan Chang, Dingyang Lyu, Xu Cai +2
Trajectory similarity is fundamental to many spatio-temporal data mining applications. Recent studies propose deep learning models to approximate conventional trajectory similarity…
DualCast: A Model to Disentangle Aperiodic Events from Traffic Series
Xinyu Su, Feng Liu, Yanchuan Chang +3
Traffic forecasting is crucial for transportation systems optimisation. Current models minimise the mean forecasting errors, often favouring periodic events prevalent in the traini…
Spatial-temporal Forecasting for Regions without Observations
Xinyu Su, Jianzhong Qi, Egemen Tanin +2
Spatial-temporal forecasting plays an important role in many real-world applications, such as traffic forecasting, air pollutant forecasting, crowd-flow forecasting, and so on. Sta…
Urban Region Representation Learning with Attentive Fusion
Fengze Sun, Jianzhong Qi, Yanchuan Chang +3
An increasing number of related urban data sources have brought forth novel opportunities for learning urban region representations, i.e., embeddings. The embeddings describe laten…
Trajectory Similarity Measurement: An Efficiency Perspective
Yanchuan Chang, Egemen Tanin, Gao Cong +2
Trajectories that capture object movement have numerous applications, in which similarity computation between trajectories often plays a key role. Traditionally, the similarity bet…