About the project
Multiple research domains ranging from physics to bio-medical research have started to incorporate simulators to answer scientific questions that have eluded us thus far due to lack of computational power and the modelling capabilities. Simulator-based inference is a computational tool that has emerged from the intersection of statistics and machine learning and that is rapidly growing. It enables to calibrate mechanistic models using computer simulations as the main tool. We will develop new efficient probabilistic surrogate models for the simulator-based inference problem. The surrogate modelling can be used in multiple ways in simulation-based inference, as it can be used to replace virtually any or all components of the stochastic simulation system. We will develop theoretical guarantees for our new methods. We will investigate whether our new methods for quantifying the difference between synthetic simulation data and observational real-world data will outperform workflow-based human-in-the-loop strategies.
Project team
Professor Jukka Corander, University of Oslo, Institute of Basic Medical Sciences
Researcher Henri Pesonen, Oslo University Hospital, Oslo Centre for Biostatistics & Epidemiology (OCBE)
Professor Robert Jenssen, UiT The Arctic University of Norway, Department of Physics and Technology
Doctoral Research Fellow Vilde Hansteen Ung, University of Oslo, Institute of Basic Medical Sciences