Materials of the Nordic Probabilistic AI School (ProbAI) 2023.

• Day 1 (June 12):

  • [recording] Helge Langseth - Opening of ProbAI 2023
  • [recording, slides, materials] Silja Renooij - Introduction to Probabilistic Models
  • [recording, slides and materials] Andrés R. Masegosa & Thomas D. Nielsen - Probabilistic Modeling and Programming Tutorial
  • [recording, slides] Arto Klami - Bette Priors for Everyone

• Day 2 (June 13):

  • [rec1, rec2, rec3, slides and materials] Helge Langseth, Andrés R. Masegosa, Thomas D. Nielsen - Variational Inference and Optimization

• Day 3 (June 14):

  • [recording, slides] Rianne van den Berg - Deep Generative Models 1
  • [recording, slides] and [material] Chin-Wei Huang & Victor Garcia Satorras - Workshop on Diffusion Models for Molecule Generation

• Day 4 (June 15):

  • [recording, slides, lectures notes] Yingzhen Li - Introduction to Bayesian Neural Networks
  • [recording, slides, notebook, materials] Andrew R. Johnson - Bayesian Workflow

• Day 5 (June 16):

  • [recording, slides and notebooks] Adèle H. Ribeiro - Causal Inference
  • [recording, slides, notebook, materials] Fredrik D. Johansson - Causal Machine Learning
  • [recording] David Baumgartner - Closing of ProbAI 2023

https://github.com/probabilisticai/dt8122-2023