[ABE-L] Nordic Probabilistic AI School 2022

[Eliezer Silva]

Prezados,

Estamos organizando uma escola de verão com ênfase em modelagem
probabilística em aprendizado de máquina / inteligência artificial que
acontecerá em Helsinki, dos dias 13 a 17 de Junho. As inscrições vão
até dia 27 de Março AoE (Anywhere on Earth). Existem um número limitado de
bolsas disponíveis pra participantes de grupos/países sub-representados,
mais informações abaixo.


Eliezer de Souza da Silva
Postdoctoral researcher at CHAIN -NTNU
Data Scientist at Clarify
Program Director at Probabilistic AI
https://eliezersilva.blog/
-------------
Nordic Probabilistic AI School (ProbAI) — June 13-17, 2022

You are welcome to apply for the Nordic Probabilistic AI School
<https://probabilistic.ai/?utm_source=aaltodoc> (ProbAI) 2022 being held on
June 13-17 in Helsinki (Finland).

APPLY NOW <https://probabilistic.ai/application/?utm_source=br> — The
application deadline is March 27.

https://probabilistic.ai/application/
About ProbAI 2022

The mission of the third Nordic Probabilistic AI School (ProbAI) is to
provide an inclusive education environment serving state-of-the-art
expertise in machine learning and artificial intelligence. The public,
students, academia and industry are welcome to join ProbAI 2022.

ProbAI is an intermediate to advanced level "summer" school with the focus
on probabilistic machine learning. Covered are topics such as probabilistic
models, variational approximations, deep generative models, latent variable
models, normalizing flows, neural ODEs, probabilistic programming, and much
more.

The ProbAI 2022 was brought to you in collaboration with University of
Helsinki <https://www.helsinki.fi/en>, FCAI <https://fcai.fi/>, Norwegian
Open AI Lab <https://www.ntnu.edu/ailab> and NTNU <https://www.ntnu.edu/>.
Program

Together with the team of invited lecturers, we intend to provide an
efficient and quality knowledge transfer through a mix of theory and
hands-on sessions, and with help of teaching assistants.

   -

   Introduction and Motivation
   -

      Arto Klami <https://scholar.google.com/citations?user=v8PeLGgAAAAJ>
      (University of Helsinki)


   -

   Luigi Acerbi <https://scholar.google.co.uk/citations?user=QYBZoGwAAAAJ>
   (University of Helsinki)


   -

   Introduction to Probabilistic Models
   -

      Antonio Salmerón
      <https://scholar.google.com/citations?user=41enG0oAAAAJ> (University
      of Almería)
      -

   Probabilistic Modeling and Programming
   -

      Andrés R. Masegosa
      <https://scholar.google.no/citations?user=J1zoY7AAAAAJ> (University
      of Almería)
      -

      Thomas Dyhre Nielsen
      <https://scholar.google.com/citations?user=6fWF0CgAAAAJ> (Aalborg
      University)
      -

   Bayesian Workflow
   -

      Elizaveta Semenova
      <https://scholar.google.com/citations?user=jqGIgFEAAAAJ> (University
      of Oxford & Imperial College London)
      -

   Variational Inference and Optimization
   -

      Andrés R. Masegosa
      <https://scholar.google.no/citations?user=J1zoY7AAAAAJ> (University
      of Almería)
      -

      Thomas Dyhre Nielsen
      <https://scholar.google.com/citations?user=6fWF0CgAAAAJ> (Aalborg
      University)
      -

      Helge Langseth
      <https://scholar.google.com/citations?user=yyXvuZsAAAAJ> (NTNU)
      -

   Deep Generative Models
   -

      Rianne van den Berg
      <https://scholar.google.com/citations?user=KARgiboAAAAJ> (Microsoft
      Research)
      -

   Normalizing Flows
   -

      Didrik Nielsen
      <https://scholar.google.com/citations?user=-sbw1JIAAAAJ> (Technical
      University of Denmark)
      -

   Gaussian Processes
   -

      Arno Solin <https://scholar.google.com/citations?user=U_fJCnAAAAAJ>
      (Aalto University)
      -

   Neural ODEs
   -

      Çağatay Yıldız
      <https://scholar.google.fi/citations?user=dNloPBUAAAAJ&hl=en> (Aalto
      University)
      -

   Simulator-Based Inference (Concept + ELFI Tutorial)
   -

      Henri Pesonen <https://scholar.google.com/citations?user=QS3yn7gAAAAJ>
      (University of Oslo)
      -

   Human-Centric ML
   -

      Fani Deligianni
      <https://scholar.google.com/citations?user=Uw6VosgAAAAJ> (Glasgow
      University)
      -

   Bayesian Neural Networks (with VI flavor)
   -

      Yingzhen Li <https://scholar.google.com/citations?user=gcfs8N8AAAAJ>
      (Imperial College London)
      -

   Bayesian Neural Networks (Advanced)
   -

      José Miguel Hernández-Lobato
      <https://scholar.google.com/citations?user=BEBccCQAAAAJ> (University
      of Cambridge)

The program may receive updates.
Registration Fee

   -

   Students (including PhD) → 250 EUR
   -

   Academia → 500 EUR
   -

   Industry → 1000 EUR

The ProbAI school has available scholarships if the registration fee or
travel costs may prevent you from attending the school. Our scholarships
are aimed primarily for applicants from developing countries and
under-represented groups.

The registration fee includes all courses, coffee breaks, lunches and
banquet.
Organizers

The 2022 edition of the Nordic Probabilistic AI School (ProbAI) is being
hosted by the University of Helsinki <https://www.helsinki.fi/en> and
organized with the support of Finnish Center for Artificial Intelligence
<https://fcai.fi/> (FCAI), Norwegian Open AI Lab
<https://www.ntnu.edu/ailab> and Norwegian University of Science and
Technology <https://www.ntnu.edu/> (NTNU).
ContactWebsite: https://probabilistic.ai
<https://probabilistic.ai/?utm_source=ml-news>
Twitter: https://twitter.com/probabilisticai/
Facebook: https://www.facebook.com/probabilisticai/
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