The aim of this work is to give an introduction for a non-practical reader to the growing field
of quantum machine learning, which is a recent discipline that combines the research areas …

Quantum Machine Learning bridges the gap between abstract developments in quantum
computing and the applied research on machine learning. Paring down the complexity of the …

Much of our understanding of human thinking is based on probabilistic models. This
innovative book by Jerome R. Busemeyer and Peter D. Bruza argues that, actually, the …

There has always been a steady interest in how humans make decisions amongst
researchers from various fields. Based on this interest, many approaches such as rational …

Research into corpus-based semantics has focused on the development of ad hoc models
that treat single tasks, or sets of closely related tasks, as unrelated challenges to be tackled …

In this paper we address the problem of modeling compositional meaning for phrases and
sentences using distributional methods. We experiment with several possible combinations …

The broader scope of our investigations is the search for the way in which concepts and their
combinations carry and influence meaning and what this implies for human thought. More …

Following an early claim by Nelson and McEvoy suggesting that word associations can
display 'spooky action at a distance behaviour', a serious investigation of the potentially …

One of the main challenges of cognitive science is to explain the representation of
conceptual knowledge and the mechanisms involved in evaluating the similarities between …

Conceptual combination performs a fundamental role in creating the broad range of
compound phrases utilised in everyday language. While the systematicity and productivity of …