|Online Variational Message Passing in Hierarchical Autoregressive Models
|Albert Podusenko, Wouter Marco Kouw, Bert de Vries, Eindhoven University of Technology, Netherlands
|G.1: Graph Analytics
|Graphs, Games, Sparsity, and Signal Processing
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|Hierarchical autoregressive (AR) models can describe many complex physical processes. Unfortunately, online adaptation in these models under non-stationary conditions remains a challenge. In this paper, we track states and parameters in a hierarchical AR filter by means of variational message passing (VMP) in a factor graph. We derive VMP update rules for an "AR node” that can be re-used at various hierarchical levels and supports automated message passing-based inference for states and parameters. The proposed method is experimentally validated for a 2-level hierarchical AR model.