4 papers
Closed-form predictive coding via hierarchical Gaussian filters
Aleksandrs Baskakovs, Sylvain Estebe, Kenneth Enevoldsen +3
Predictive coding (PC) offers a local and biologically grounded alternative to backpropagation in the training of artificial neural networks, yet to date, it remains slower, and pe…
Robust volatility updates for Hierarchical Gaussian Filtering
Christoph Mathys, Nicolas Legrand, Peter Thestrup Waade +2
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…
Improving reasoning at inference time via uncertainty minimisation
Nicolas Legrand, Kenneth Enevoldsen, Márton Kardos +1
Large language models (LLMs) now exhibit strong multi-step reasoning abilities, but existing inference-time scaling methods remain computationally expensive, often relying on exten…
The generalized Hierarchical Gaussian Filter
Lilian Aline Weber, Peter Thestrup Waade, Nicolas Legrand +3
Hierarchical Bayesian models of perception and learning feature prominently in contemporary cognitive neuroscience where, for example, they inform computational concepts of mental…