Chen Zhang

Orcid: 0000-0002-4767-9597

Affiliations:
  • Tsinghua University, Beijing, China
  • National University of Singapore, Department of Industrial and Systems Engineering, Singapore (former)


According to our database1, Chen Zhang authored at least 25 papers between 2014 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2023
A Hidden Markov Model for Condition Monitoring of Time Series Data in Complex Network Systems.
IEEE Trans. Reliab., December, 2023

Deep Cascade-Learning Model via Recurrent Attention for Immunofixation Electrophoresis Image Analysis.
IEEE Trans. Medical Imaging, December, 2023

A Cluster-Oriented Bayesian Network Approach for Mixed-Type Event Prediction With Application in Order Logistics.
IEEE Trans. Ind. Informatics, October, 2023

Multi-view metro station clustering based on passenger flows: a functional data-edged network community detection approach.
Data Min. Knowl. Discov., May, 2023

A Bayesian Partially Observable Online Change Detection Approach with Thompson Sampling.
Technometrics, April, 2023

Tensor Dirichlet Process Multinomial Mixture Model for Passenger Trajectory Clustering.
CoRR, 2023

MM-DAG: Multi-task DAG Learning for Multi-modal Data - with Application for Traffic Congestion Analysis.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Tensor Dirichlet Process Multinomial Mixture Model with Graphs for Passenger Trajectory Clustering.
Proceedings of the 6th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, 2023

Dynamic Causal Graph Convolutional Network for Traffic Prediction.
Proceedings of the 19th IEEE International Conference on Automation Science and Engineering, 2023

2022
Segment-Wise Time-Varying Dynamic Bayesian Network with Graph Regularization.
ACM Trans. Knowl. Discov. Data, 2022

A Data-Driven Method for Online Monitoring Tube Wall Thinning Process in Dynamic Noisy Environment.
IEEE Trans Autom. Sci. Eng., 2022

Individualized passenger travel pattern multi-clustering based on graph regularized tensor latent dirichlet allocation.
Data Min. Knowl. Discov., 2022

GRELEN: Multivariate Time Series Anomaly Detection from the Perspective of Graph Relational Learning.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021
Holistic Prediction for Public Transport Crowd Flows: A Spatio Dynamic Graph Network Approach.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Transformer Based Spatial-Temporal Fusion Network for Metro Passenger Flow Forecasting.
Proceedings of the 17th IEEE International Conference on Automation Science and Engineering, 2021

2020
Time-Warped Sparse Non-negative Factorization for Functional Data Analysis.
ACM Trans. Knowl. Discov. Data, 2020

Long-Short Term Spatiotemporal Tensor Prediction for Passenger Flow Profile.
IEEE Robotics Autom. Lett., 2020

Partially Observable Online Change Detection via Smooth-Sparse Decomposition.
CoRR, 2020

Crowding Prediction of In-Situ Metro Passengers Using Smart Card Data.
CoRR, 2020

Tensor Completion for Weakly-Dependent Data on Graph for Metro Passenger Flow Prediction.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Partially Observable Multi-Sensor Sequential Change Detection: A Combinatorial Multi-Armed Bandit Approach.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Statistical Analysis of Simulation Output from Parallel Computing.
ACM Trans. Model. Comput. Simul., 2018

Clustering Subway Station Arrival Patterns Using Weighted Dynamic Time Warping.
Proceedings of the 2018 IEEE International Conference on Industrial Engineering and Engineering Management, 2018

2015
Statistical monitoring of longitudinal categorical survey data.
Proceedings of the 2015 IEEE International Conference on Industrial Engineering and Engineering Management, 2015

2014
Robust on-line monitoring for univariate processes based on two sample goodness-of-fit test.
Proceedings of the 2014 IEEE International Conference on Industrial Engineering and Engineering Management, 2014


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