9 citations · 26 across the 8 of their papers we have counts for
8 papers
Prediction-Oriented Sequential Bayesian Design of Physical Experiments Informed by Computer Models
Hao Zhu, Markus Hainy
In many scientific and engineering domains, physical experiments are often costly, time-consuming, and limited to a certain number of design points. The Kennedy and O'Hagan (KOH) f…
Practical aspects of the virtual noise convex optimum design approach for correlated responses
Markus Hainy, Werner G. Müller, Andrej Pázman
In this paper we present several practically-oriented extensions and considerations for the virtual noise method in optimal design under correlation. First we introduce a slightly…
Active Discrimination Learning for Gaussian Process Models
Elham Yousefi, Luc Pronzato, Markus Hainy +2
The paper covers the design and analysis of experiments to discriminate between two Gaussian process models, such as those widely used in computer experiments, kriging, sensor loca…
A convex approach to optimum design of experiments with correlated observations
Andrej Pázman, Markus Hainy, Werner G. Müller
Optimal design of experiments for correlated processes is an increasingly relevant and active research topic. Present methods have restricted possibilities to judge their quality.…
Sequential Experimental Design for Predator-Prey Functional Response Experiments
Hayden Moffat, Markus Hainy, Nikos E. Papanikolaou +1
Understanding functional response within a predator-prey dynamic is a cornerstone for many quantitative ecological studies. Over the past 60 years, the methodology for modelling fu…
Optimal Bayesian design for model discrimination via classification
Markus Hainy, David J. Price, Olivier Restif +1
Performing optimal Bayesian design for discriminating between competing models is computationally intensive as it involves estimating posterior model probabilities for thousands of…
ABC model selection for spatial extremes models applied to South Australian maximum temperature data
Xing Ju Lee, Markus Hainy, James P. McKeone +2
Max-stable processes are a common choice for modelling spatial extreme data as they arise naturally as the infinite-dimensional generalisation of multivariate extreme value theory.…
Likelihood-free Simulation-based Optimal Design
Markus Hainy, Werner G. Müller, Helga Wagner
Simulation-based optimal design techniques are a convenient tool for solving a particular class of optimal design problems. The goal is to find the optimal configuration of factor…