Deep Probabilistic and Generative Modeling

Deep Probabilistic and Generative Modelling

Date: 20th May, 2026
Time: 6 PM
Where: Online

Deep probabilistic and generative models are becoming an important part of the modern machine learning toolkit, with growing applications in biomedical research and AI.

In this meetup, we’ll start with a primer on deep probabilistic modelling before exploring state-of-the-art generative approaches, including probabilistic graphical models, variational inference, diffusion models, and flow matching. The talk will also cover applications of these methods in biomedical research, followed by a short hands-on coding session introducing the basics of building a deep probabilistic model in PyTorch.
So come along if you’re interested in modern machine learning, generative AI, or computational biology, or if you’d like a practical introduction to probabilistic modelling techniques and their research applications.