Finite mixture models and hidden Markov models (HMMs) occupy central roles in modern statistical inference and data analysis. Finite mixture models assume that data originate from a latent combination ...

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Data clustering is the process of grouping data items so that similar items are placed in the same cluster. There are several different clustering techniques, and each technique has many variations.

In this paper, we introduce a Bayesian approach for clustering data using a sparse finite mixture model (SFMM). The SFMM is a finite mixture model with a large number of components k previously fixed ...

Although deep learning-based methods have demonstrated promising results in estimating the RUL, most methods consider that each time step's features hold equal importance. When data with varying ...