2 citations · 2 across the 3 of their papers we have counts for
6 papers
Bayesian spatiotemporal modeling of passenger trip assignment in metro networks
Xiaoxu Chen, Alexandra M. Schmidt, Zhenliang Ma +1
Assigning passenger trips to specific network paths using automatic fare collection (AFC) data is a fundamental application in urban transit analysis. The task is a difficult inver…
ForecastGrapher: Redefining Multivariate Time Series Forecasting with Graph Neural Networks
Wanlin Cai, Kun Wang, Hao Wu +2
The challenge of effectively learning inter-series correlations for multivariate time series forecasting remains a substantial and unresolved problem. Traditional deep learning mod…
Bayesian Inference of Time-Varying Origin-Destination Matrices from Boarding/Alighting Counts for Transit Services
Xiaoxu Chen, Zhanhong Cheng, Lijun Sun
Origin-destination (OD) demand matrices are crucial for transit agencies to design and operate transit systems. This paper presents a novel temporal Bayesian model designed to esti…
Conditional forecasting of bus travel time and passenger occupancy with Bayesian Markov regime-switching vector autoregression
Xiaoxu Chen, Zhanhong Cheng, Alexandra M. Schmidt +1
Accurately forecasting bus travel time and passenger occupancy with uncertainty is essential for both travelers and transit agencies/operators. However, existing approaches to fore…
Enhancing Representation Learning for Periodic Time Series with Floss: A Frequency Domain Regularization Approach
Chunwei Yang, Xiaoxu Chen, Lijun Sun +2
Time series analysis is a fundamental task in various application domains, and deep learning approaches have demonstrated remarkable performance in this area. However, many real-wo…
Discovering Dynamic Patterns from Spatiotemporal Data with Time-Varying Low-Rank Autoregression
Xinyu Chen, Chengyuan Zhang, Xiaoxu Chen +2
The problem of broad practical interest in spatiotemporal data analysis, i.e., discovering interpretable dynamic patterns from spatiotemporal data, is studied in this paper. Toward…