Bayesian optimisation is a statistical method that efficiently models and optimises expensive
“black-box” functions. This review considers the application of Bayesian optimisation to …

Recent years have marked a renaissance in efforts to increase research reproducibility in
psychology, neuroscience, and related fields. Reproducibility is the cornerstone of a solid …

Wearable robotic devices have been shown to substantially reduce the energy expenditure
of human walking. However, response variance between participants for fixed control …

Bayesian Optimization and Data Science Page 1 123 SPRINGER BRIEFS IN
OPTIMIZATION Francesco Archetti Antonio Candelieri Bayesian Optimization and Data …

For most neuroimaging questions the range of possible analytic choices makes it unclear
how to evaluate conclusions from any single analytic method. One possible way to address …

The increasing capabilities of exoskeletons and powered prosthetics for walking assistance
have paved the way for more sophisticated and individualized control strategies. In …

Electronically active organic molecules have demonstrated great promise as novel soft
materials for energy harvesting and transport. Self-assembled nanoaggregates formed from …

The so-called resting state, in which participants lie quietly with no particular inputs or
outputs, represented a paradigm shift from conventional task-based studies in human …

One of the most critical challenges in using noninvasive brain stimulation (NIBS) techniques
for the treatment of psychiatric and neurologic disorders is inter-and intra-individual …

This report presents an overview of how machine learning is rapidly advancing clinical
translational imaging in ways that will aid in the early detection, prediction, and treatment of …