Posterior inference with an intractable likelihood is becoming an increasingly common task
in scientific domains which rely on sophisticated computer simulations. Typically, these …

Recent advances in connectomics research enable the acquisition of increasing amounts of
data about the connectivity patterns of neurons. How can we use this wealth of data to …

Many scientific models are composed of multiple discrete components, and scientists often
make heuristic decisions about which components to include. Bayesian inference provides a …

This dissertation presents several novel techniques and guidelines to advance the field of
simulation-based inference. Simulation-based inference, or likelihood-free inference, refers …

The brain is composed of an intricately connected network of cells—what are the factors that
con-38 tribute to constructing these patterns of connectivity, and how? To answer these …