How can a machine learn from experience? Probabilistic modelling provides a framework
for understanding what learning is, and has therefore emerged as one of the principal …

In recent years, deep learning has revolutionized the field of machine learning, for computer
vision in particular. In this approach, a deep (multilayer) artificial neural network (ANN) is …

How is it that thoroughly physical material beings such as ourselves can think, dream, feel,
create and understand ideas, theories and concepts? How does mere matter give rise to all …

The first comprehensive treatment of active inference, an integrative perspective on brain,
cognition, and behavior used across multiple disciplines. Active inference is a way of …

A new theory is taking hold in neuroscience. It is the theory that the brain is essentially a
hypothesis-testing mechanism, one that attempts to minimise the error of its predictions …

Brains, it has recently been argued, are essentially prediction machines. They are bundles
of cells that support perception and action by constantly attempting to match incoming …

We consider several key aspects of prediction in language comprehension: its
computational nature, the representational level (s) at which we predict, whether we use …

The Phenomenological Mind, Third Edition introduces fundamental questions about the
mind from the perspective of phenomenology. One of the outstanding books in the field, now …

After growing up together, and mostly growing apart in the second half of the 20th century,
the fields of artificial intelligence (AI), cognitive science, and neuroscience are reconverging …

This review considers computational psychiatry from a particular viewpoint: namely, a
commitment to explaining psychopathology in terms of pathophysiology. It rests on the …