4 papers
Online Generalised Predictive Coding
Mehran H. Z. Bazargani, Szymon Urbas, Adeel Razi +2
This paper introduces an extension of generalised filtering for online applications. Generalised filtering refers to data assimilation schemes that jointly infer latent states, lea…
Brain in the Dark: Design Principles for Neuromimetic Inference under the Free Energy Principle
Mehran H. Bazargani, Szymon Urbas, Karl Friston
Deep learning has revolutionised artificial intelligence (AI) by enabling automatic feature extraction and function approximation from raw data. However, it faces challenges such a…
Brain in the Dark: Design Principles for Neuro-mimetic Learning and Inference
Mehran H. Bazargani, Szymon Urbas, Karl Friston
Even though the brain operates in pure darkness, within the skull, it can infer the most likely causes of its sensory input. An approach to modelling this inference is to assume th…
Predicting milk traits from spectral data using Bayesian probabilistic partial least squares regression
Szymon Urbas, Pierre Lovera, Robert Daly +3
High-dimensional spectral data -- routinely generated in dairy production -- are used to predict a range of traits in milk products. Partial least squares (PLS) regression is ubiqu…