Trustworthy AI: Bayesian deep learning | AI FOR GOOD DISCOVERY

Bayesian models are rooted in Bayesian statistics and easily benefit from the vast literature in the field. In contrast, deep learning lacks a solid mathematical grounding. Instead, empirical developments in deep learning are often justified by metaphors, evading the unexplained principles at play. These two fields are perceived as fairly antipodal to each other in their respective communities. It is perhaps astonishing then that most modern deep learning models can be cast as performing approximate inference in a Bayesian setting. The implications of this are profound: we can use the rich Bayesian statistics literature with deep learning models, explain away many of the curiosities with ad hoc techniques, combine results from deep learning into Bayesian modelling, and much more. In this talk, Yarin Gal will discuss interesting advances in the field. 🔴 Watch the latest #AIforGood videos: Explore more #AIforGood content: 1️⃣