We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
1 This papers introduces a generic framework for OBDD variants with weighted edges. It covers many boolean and multi-valued OBDD-variants that have been studied in the literature a...
The purpose of this note is to describe the underlying insights and results obtained by the authors, and others, in a series of papers aimed at modelling the distribution of `natu...
In this paper we survey work being conducted at Imperial College on the use of machine learning to build Systems Biology models of the effects of toxins on biochemical pathways. Se...