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An Efficient Implementation for Spatial-Temporal Gaussian Process Regression and Its Applications
Spatial-temporal Gaussian process regression is a popular method for spatial-temporal data modeling.
Asymptotic Theory for Regularized System Identification Part I: Empirical Bayes Hyper-parameter Estimator
Regularized system identification is the major advance in system identification in the last decade.
ChunkFormer: Learning Long Time Series with Multi-stage Chunked Transformer
In this way, the proposed model gradually learns both local and global information without changing the total length of the input sequences.
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