131 citations · 200 across the 8 of their papers we have counts for
5 papers · 1 filter
Data-driven Prior Learning for Bayesian Optimisation
Sigrid Passano Hellan, Christopher G. Lucas, Nigel H. Goddard
Transfer learning for Bayesian optimisation has generally assumed a strong similarity between optimisation tasks, with at least a subset having similar optimal inputs. This assumpt…
Bayesian Optimisation Against Climate Change: Applications and Benchmarks
Sigrid Passano Hellan, Christopher G. Lucas, Nigel H. Goddard
Bayesian optimisation is a powerful method for optimising black-box functions, popular in settings where the true function is expensive to evaluate and no gradient information is a…
Bayesian Optimisation for Active Monitoring of Air Pollution
Sigrid Passano Hellan, Christopher G. Lucas, Nigel H. Goddard
Air pollution is one of the leading causes of mortality globally, resulting in millions of deaths each year. Efficient monitoring is important to measure exposure and enforce legal…
Optimising Placement of Pollution Sensors in Windy Environments
Sigrid Passano Hellan, Christopher G. Lucas, Nigel H. Goddard
Air pollution is one of the most important causes of mortality in the world. Monitoring air pollution is useful to learn more about the link between health and pollutants, and to i…
Non-Intrusive Load Monitoring with Fully Convolutional Networks
Cillian Brewitt, Nigel Goddard
Non-intrusive load monitoring or energy disaggregation involves estimating the power consumption of individual appliances from measurements of the total power consumption of a home…