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ProbAI 2021

Materials of the Nordic Probabilistic AI School (ProbAI) 2021.

Lectures and Tutorials

  • Day 1 (June 14):
    • [materials] Antonio Salmerón - Introduction to Probabilistic Models
    • [materials] Andrés R. Masegosa & Thomas D. Nielsen - Probabilistic Programming
  • Day 2 (June 15):
    • [slides] Arto Klami – Variational Inference and Optimization (part 1)
    • [materials] Andrés R. Masegosa & Thomas D. Nielsen – Variational Inference and Probabilistic Programming (part 1)
  • Day 3 (June 16):
    • [slides] Evrim Acar Ataman – Tensor Factorizations for Physical, Chemical, and Biological Systems
    • [slides] Arto Klami – Variational Inference and Optimization (part 2)
    • [materials] Andrés R. Masegosa & Thomas D. Nielsen – Variational Inference and Probabilistic Programming (part 2)
  • Day 4 (June 17):
    • [slides] Wilker Aziz - Deep Discrete Latent Variable Models
    • [notebook, slides] Francisco J. R. Ruiz - Variational Inference with Implicit and Semi-Implicit Distributions
  • Day 5 (June 18):
    • [slides] Mihaela Rosca - How to Build a GAN Loss from Distributional Divergences and Distances
    • [slide, notebook [solution]] Didrik Nielsen - Normalizing Flows
    • [notebook] Çağatay Yıldız - Neural ODE & ODE2VAE