We present sbi reloaded, a comprehensive update to the sbi Python package that provides researchers with state-of-the-art algorithms and tools for simulation-based inference workflows across scientific domains.
Internal seminar at TransferLab discussing recent advances in simulation-based inference methods and their practical applications across scientific domains.
Hands-on training in Simulation-Based Inference (SBI), designed for applications in neuroscience, astrophysics, and biology. Developed in collaboration with the University of Tübingen and the TransferLab at the appliedAI Institute for Europe.
sbi is a Python package for simulation-based inference, providing a user-friendly interface to perform Bayesian parameter inference for simulator-based models with intractable likelihoods.