AI RESEARCH
Robust volatility updates for Hierarchical Gaussian Filtering
arXiv CS.LG
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ArXi:2605.00966v1 Announce Type: new Hierarchical Gaussian Filtering (HGF) networks allow for efficient updating of posterior distributions (beliefs) about hidden states of an agent's environment. HGF parent nodes can target the mean or variance of their children. New information entering at input nodes leads to a cascade of belief updates across the network according to one-step update equations for each node's mean and precision (inverse variance