The SBI (Simulation-Based Inference) toolbox was initially developed by the team of our core-faculty member Jakob Macke in 2020 and has since become a community project maintained by several labs worldwide. The SBI Toolbox aims to bridge the gap between theoretical models and real-world data, by allowing researchers to tune the parameters of mechanistic models to align with empirical observations. The hackathon brought together scientists that aimed to enhance the SBI Toolbox by discussing its scope, introducing new features and expanding its capabilities.
What are possible applications of SBI?
SBI has been successfully applied in a variety of scientific disciplines, including neuroscience, climate science, and astronomy. It is also an active area of research, with new methods being developed to make SBI applicable to a wider range of problems. We hope to incorporate these new methods into our toolbox, so stay tuned!