11 citations · 14 across the 4 of their papers we have counts for
5 papers
A Unified Probabilistic Framework for Spatiotemporal Passenger Crowdedness Inference within Urban Rail Transit Network
Min Jiang, Andi Wang, Ziyue Li +1
This paper proposes the Spatio-Temporal Crowdedness Inference Model (STCIM), a framework to infer the passenger distribution inside the whole urban rail transit (URT) system in rea…
Handling Missing Data via Max-Entropy Regularized Graph Autoencoder
Ziqi Gao, Yifan Niu, Jiashun Cheng +6
Graph neural networks (GNNs) are popular weapons for modeling relational data. Existing GNNs are not specified for attribute-incomplete graphs, making missing attribute imputation…
Long-Short Term Spatiotemporal Tensor Prediction for Passenger Flow Profile
Ziyue Li, Hao Yan, Chen Zhang +1
Spatiotemporal data is very common in many applications, such as manufacturing systems and transportation systems. It is typically difficult to be accurately predicted given intrin…
Tensor Completion for Weakly-dependent Data on Graph for Metro Passenger Flow Prediction
Ziyue Li, Nurettin Dorukhan Sergin, Hao Yan +2
Low-rank tensor decomposition and completion have attracted significant interest from academia given the ubiquity of tensor data. However, the low-rank structure is a global proper…
Optimal Sequential Tests for Monitoring Changes in the Distribution of Finite Observation Sequences
Dong Han, Fugee Tsung, Jinguo Xian
This article develops a method to construct the optimal sequential test for monitoring the changes in the distribution of finite observation sequences with a general dependence str…