July 28, 2014
"Uncertainty in Computer Models 2014" will bring together international researchers who are trying to address this question and related problems. DATADVANCE is attending the conference with the paper on "Learning Gaussian Process Regression from Data with Factorial Structure" presented by Evgeny Burnaev, head of Intellectual Data Analysis Department, DATADVANCE.
The conference focuses on statistical methods to quantify and analyse the uncertainties in the predictions of computer models. Uncertainty in Computer Models 2014 will address all aspects of model uncertainty, both theoretical and practical.
This conference is an initiative of the MUCM (Managing Uncertainty in Complex Models) project. Research in MUCM is concerned with all aspects of uncertainty in computer models, including the propagation of parameter uncertainty, model discrepancy, validation, sensitivity analysis and the calibration of models. Uncertainty in computer models is an emerging and highly topical field of statistical research, with many challenges and an enormous range of applications.