Silvan C. Quax

This study uses a neural network model to show how neurons represent and incorporate prior knowledge through environmental regularities, without probabilistic feedback.

This study introduces a recurrent neural network with adaptive time scales, showing improved performance in temporal prediction and memory capacity.

This paper introduces a recurrent generative model that mimics human visual attention by minimizing predictive uncertainty through saccadic eye movements.

This paper introduces a Bayesian approach to population receptive field mapping in fMRI data to quantify uncertainty in receptive field properties.