Now showing items 1-5 of 5
Transfer learning with Gaussian processes
(The University of Edinburgh, 2012-06-25)
Transfer Learning is an emerging framework for learning from data that aims at intelligently transferring information between tasks. This is achieved by developing algorithms that can perform multiple tasks simultaneously, ...
Variational inference for Gaussian-jump processes with application in gene regulation
(The University of Edinburgh, 2013-11-28)
In the last decades, the explosion of data from quantitative techniques has revolutionised our understanding of biological processes. In this scenario, advanced statistical methods and algorithms are becoming fundamental ...
Input-output transformations in the awake mouse brain using whole-cell recordings and probabilistic analysis
(The University of Edinburgh, 2015-11-26)
The activity of cortical neurons in awake brains changes dynamically as a function of the behavioural and attentional state. The primary motor cortex (M1) plays a central role in regulating complex motor behaviors. Despite ...
Impaired reinforcement learning and Bayesian inference in psychiatric disorders: from maladaptive decision making to psychosis in schizophrenia
(The University of Edinburgh, 2015-06-29)
Computational modelling has been gaining an increasing amount of support from the neuroscience community as a tool to assay cognition and computational processes in the brain. Lately, scientists have started to apply ...
Acquisition and influence of expectations about visual speed
(The University of Edinburgh, 2016-06-27)
It has been long hypothesized that due to the inherent ambiguities of visual input and the limitations of the visual system, vision is a form of “unconscious inference” whereby the brain relies on assumptions (aka ...