2 papers
stat.ME2025
Tensor-variate Gaussian process regression for efficient emulation of complex systems: comparing regressor and covariance structures in outer product and parallel partial emulators
Daria Semochkina, Samuel E. Jackson, David C. Woods
Multi-output Gaussian process regression has become an important tool in uncertainty quantification, for building emulators of computationally expensive simulators, and other areas…
stat.ME2024
Multi-objective optimisation using expected quantile improvement for decision making in disease outbreaks
Daria Semochkina, Alexander I. J. Forrester, David C Woods
Optimization under uncertainty is important in many applications, particularly to inform policy and decision making in areas such as public health. A key source of uncertainty aris…