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  1. 1
    Learning Model Predictive Control Parameters via Bayesian Optimization for Battery Fast Charging

    Learning Model Predictive Control Parameters via Bayesian Optimization for Battery Fast Charging by Hirt, Sebastian, Höhl, Andreas, Schaeffer, Joachim, Pohlodek, Johannes, Braatz, Richard D, Findeisen, Rolf

    Published 2024
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    Article
  2. 2
    Unsupervised bayesian generative methods

    Unsupervised bayesian generative methods by Li, Shaohua

    Published 2016
    “…Experimental results show that FAB-FHMM significantly outperforms state-of-the-art nonparametric Bayesian iFHMM and Variational FHMM, in terms of model selection accuracy and held-out perplexity. 2) The model selection process of FAB is explained by the proof of a novel “winner-take-all” theorem. 3) It is proved that under certain conditions, the FIC regularization is equivalent to the Chinese Restaurant Process (CRP) prior, a popular Bayesian nonparametric prior. …”
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    Thesis

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