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08/24/2023
A Co-training Approach for Noisy Time Series Learning
In this work, we focus on robust time series representation learning. Ou...
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06/23/2023
Tensor Dirichlet Process Multinomial Mixture Model for Passenger Trajectory Clustering
Passenger clustering based on travel records is essential for transporta...
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06/14/2023
A Unified Probabilistic Framework for Spatiotemporal Passenger Crowdedness Inference within Urban Rail Transit Network
This paper proposes the Spatio-Temporal Crowdedness Inference Model (STC...
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06/12/2023
Correlated Time Series Self-Supervised Representation Learning via Spatiotemporal Bootstrapping
Correlated time series analysis plays an important role in many real-wor...
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06/05/2023
MM-DAG: Multi-task DAG Learning for Multi-modal Data – with Application for Traffic Congestion Analysis
This paper proposes to learn Multi-task, Multi-modal Direct Acyclic Grap...
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04/10/2023
Missing Data Imputation with Graph Laplacian Pyramid Network
Data imputation is a prevalent and important task due to the ubiquitousn...
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01/30/2023
Robust Attributed Graph Alignment via Joint Structure Learning and Optimal Transport
Graph alignment, which aims at identifying corresponding entities across...
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11/30/2022
Handling Missing Data via Max-Entropy Regularized Graph Autoencoder
Graph neural networks (GNNs) are popular weapons for modeling relational...
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06/26/2022
Latent Augmentation For Better Graph Self-Supervised Learning
Graph self-supervised learning has been vastly employed to learn represe...
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11/04/2021
Robust Online Detection in Serially Correlated Directed Network
As the complexity of production processes increases, the diversity of da...
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04/23/2020
Long-Short Term Spatiotemporal Tensor Prediction for Passenger Flow Profile
Spatiotemporal data is very common in many applications, such as manufac...
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12/11/2019
Tensor Completion for Weakly-dependent Data on Graph for Metro Passenger Flow Prediction
Low-rank tensor decomposition and completion have attracted significant ...
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07/31/2019
