Julian Eisenschlos: Know what you don't know, Tools to understand uncertainty in DL | PyData Crdoba

In this talk, we want to bridge the gap between practical methods for Deep Learning and Bayesian Inference in a practical setting. As motivation, we will start by introducing common problems in machine learning systems that arise from the lack of understanding of how uncertain models are when given specific inputs. This causes limitations on applications that need robust solutions and can impact people lives, such as healthcare, financial trading, and autonomous vehicles. We will present Bayesian Neural N