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Individual passenger travel patterns have significant value in understanding passenger’s behavior, such as learning the hidden …

A tensor voting-based surface anomaly classification approach by using 3D point cloud data

Adaptive partially observed sequential change detection and isolation

Bayesian spatio-temporal graph transformer network (b-star) for multi-aircraft trajectory prediction

Convolutional neural network-assisted adaptive sampling for sparse feature detection in image and video data

Deep spatio-temporal sparse decomposition for trend prediction and anomaly detection in cardiac electrical conduction

Tensor latent Dirichlet allocation with graph regularization for passenger travel patterns.

Multi-task learning with latent variation decomposition for multivariate responses in a manufacturing network

Profile decomposition based hybrid transfer learning for cold-start data anomaly detection

Rapid detection of hot-spots via tensor decomposition with applications to crime rate data