20-22 September 2021
Online via Zoom
Europe/Berlin timezone

You use simulation in physics, economics, archaeology or any other domain of your choice? You want to find the simulator's parameters that best fits the observations? Then simulation-based inference is something for you!

We teach a practical simulation-based inference workshop to help you understand recent machine learning techniques and apply them to your problem. We plan to cover the following topics:

  • Day 1: Using simulators for discovery, introduction to conditional density estimation.
    • a discussion of simulators
    • parameter inference
    • Bayesian Inference without Likelihoods
  • Day 2: How does neural simulation-based inference work?
    • Bayes' Rule with neural density estimators
    • posterior estimation (SNPE)
    • likelihood estimation (SNLE and beyond)
  • Day 3: Applying the sbi toolbox to your problem. Pitfalls, tricks and opportunities!
    • hands-on: sbi
    • hands-on: sbi and normalizing flows
    • hands-on: calibration or misspecification
    • bring your own data

Apply to learn, have fun, and participate in a supportive and inclusive community. The workshop will combine lectures and practical hands-on sessions by experts in the field. We strive to provide a seamless computing environment for you to focus on the content rather than in import errors.

Interested?

Apply for the workshop by filling out the registration form! In case the course is already booked out, please consider signing up to the waiting list.

When & Where?

20-22 September, 9am - 5pm CEST

We will circulate the zoom link to all accepted learners.

Any other Questions?

Join our simulation-based inference discussion forum in Zulip (you are welcome whether a participant or not!)
    

Instructors and Support

Jan-Matthis Lückmann

Jan-Matthis Lückmann
mackelab @ Tübingen University

Daniela Huppenkothen

Daniela Huppenkothen
SRON Netherlands Institute for Space Research

David Greenberg

David Greenberg
Helmholtz AI & Helmholtz-Zentrum Hereon

Jan Bölts

Jan Bölts
mackelab @ Tübingen University

Michael Deistler

Michael Deistler
mackelab @ Tübingen University

Peter Steinbach

Peter Steinbach
Helmholtz AI & Helmholtz-Zentrum Dresden-Rossendorf

Álvaro Tejero-Cantero

Álvaro Tejero-Cantero
mlcolab @ Tübingen University

Pedro J. Gonçalves

Pedro J. Gonçalves
mackelab @ caesar

 

Organisational Team

Álvaro Tejero-Cantero

Álvaro Tejero-Cantero
mlcolab @ Tübingen University

Elena Sizana

Elena Sizana
mlcolab @ Tübingen University

Stefan Wezel

Stefan Wezel
mlcolab @ Tübingen University

Peter Steinbach

Peter Steinbach
Helmholtz AI & Helmholtz-Zentrum Dresden-Rossendorf

Supporting Organisations

Helmholtz AI

mlcolab

mlcolab

Starts
Ends
Europe/Berlin
Online via Zoom
Registration
Registration for this event is currently open.