11 citations · 15 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Distribution-aware Online Continual Learning for Urban Spatio-Temporal Forecasting
Chengxin Wang, Gary Tan, Swagato Barman Roy +1
Urban spatio-temporal (ST) forecasting is crucial for various urban applications such as intelligent scheduling and trip planning. Previous studies focus on modeling ST correlation…
cs.LG2021★ 11 cited
Periodic Residual Learning for Crowd Flow Forecasting
Chengxin Wang, Yuxuan Liang, Gary Tan
Crowd flow forecasting, which aims to predict the crowds entering or leaving certain regions, is a fundamental task in smart cities. One of the key properties of crowd flow data is…
cs.CV2020★ 4 cited
GraphTCN: Spatio-Temporal Interaction Modeling for Human Trajectory Prediction
Chengxin Wang, Shaofeng Cai, Gary Tan
Predicting the future paths of an agent's neighbors accurately and in a timely manner is central to the autonomous applications for collision avoidance. Conventional approaches, e.…