17 citations · 64 across the 23 of their papers we have counts for
5 papers · 1 filter
The Bayesian Context Trees State Space Model for time series modelling and forecasting
Ioannis Papageorgiou, Ioannis Kontoyiannis
A hierarchical Bayesian framework is introduced for developing tree-based mixture models for time series, partly motivated by applications in finance and forecasting. At the top le…
Truly Bayesian Entropy Estimation
Ioannis Papageorgiou, Ioannis Kontoyiannis
Estimating the entropy rate of discrete time series is a challenging problem with important applications in numerous areas including neuroscience, genomics, image processing and na…
Posterior Representations for Bayesian Context Trees: Sampling, Estimation and Convergence
Ioannis Papageorgiou, Ioannis Kontoyiannis
We revisit the Bayesian Context Trees (BCT) modelling framework for discrete time series, which was recently found to be very effective in numerous tasks including model selection,…
Context-tree weighting for real-valued time series: Bayesian inference with hierarchical mixture models
Ioannis Papageorgiou, Ioannis Kontoyiannis
Real-valued time series are ubiquitous in the sciences and engineering. In this work, a general, hierarchical Bayesian modelling framework is developed for building mixture models…
Bayesian Context Trees: Modelling and exact inference for discrete time series
Ioannis Kontoyiannis, Lambros Mertzanis, Athina Panotopoulou +2
We develop a new Bayesian modelling framework for the class of higher-order, variable-memory Markov chains, and introduce an associated collection of methodological tools for exact…