Teaching

• Introduction to Probabilistic Graphical Models Teaching Assistant
  
  M2 Mathématiques, Vision, Apprentissage - ENS Paris Saclay (2023 – 2026)

  This course provides a unifying introduction to probabilistic modelling through the framework of graphical models, together with their associated learning and inference algorithms. It is an historical course at the core of the MVA program. Recent developments in mathematics are largely covered. In particular, this course cover deep latent variable models, variational autoencoders, energy based models, score-based diffusion models, amortised inference, and causal inference.