131 citations · 200 across the 8 of their papers we have counts for
8 papers
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…
Sequence-to-point learning with neural networks for nonintrusive load monitoring
Chaoyun Zhang, Mingjun Zhong, Zongzuo Wang +2
Energy disaggregation (a.k.a nonintrusive load monitoring, NILM), a single-channel blind source separation problem, aims to decompose the mains which records the whole house electr…
Latent Bayesian melding for integrating individual and population models
Mingjun Zhong, Nigel Goddard, Charles Sutton
In many statistical problems, a more coarse-grained model may be suitable for population-level behaviour, whereas a more detailed model is appropriate for accurate modelling of ind…
Interleaved Factorial Non-Homogeneous Hidden Markov Models for Energy Disaggregation
Mingjun Zhong, Nigel Goddard, Charles Sutton
To reduce energy demand in households it is useful to know which electrical appliances are in use at what times. Monitoring individual appliances is costly and intrusive, whereas d…