Soft-BCT extends Bayesian context trees to real-valued time series with soft probabilistic splits learned via variational inference and shows better performance than prior hard-split BCT on some datasets.
An analysis of the difference of code lengths between two-step codes based on MDL principle and Bayes codes
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Soft Bayesian Context Tree Models for Real-Valued Time Series
Soft-BCT extends Bayesian context trees to real-valued time series with soft probabilistic splits learned via variational inference and shows better performance than prior hard-split BCT on some datasets.