Valentin Pratz

I am a master’s student at Heidelberg University. I specialize in computational physics, with a focus on statistics and scientific machine learning. A foray into psychology sparked my interest in scientific modeling and Bayesian statistics. Advancing modern Bayesian methods has since been my primary research focus. The BayesFlow team introduced me to amortized Bayesian inference (ABI) and the ways it can benefit from machine learning. I have since become a contributor and a co-maintainer of the project. I have contributed to various paper in this research area, and regularly blog about ongoing development and research. Our methods are not specific to a certain field, but many practitioners are new to machine learning methods. Therefore supporting users and writing documentation are important to me as well, to make the results of our research as accessible as possible.