Explainability in Machine Learning

March 28-29th, 2023  |  Alte Aula, Tübingen, Germany




Deep learning has enabled major advances in machine learning. However, the deployment of deep learning frameworks in settings that are safety-critical or that impact society requires their decision-making to be explainable. This is fundamental for building trustworthy and user-oriented machine learning models. The aim of this workshop is to generate awareness around explainability in machine learning which is a topic of growing interest. Furthermore, we aim to encourage interdisciplinary interaction and collaboration between researchers from the University of Tübingen and other international institutions that work on different aspects of explainability, in particular in the context of computer vision.


Our workshop will consider research on approaches to explainability and on applications of explainability. Topics of interest will include (but will not be limited to):

  • Computer vision (and visual explanations)
  • Natural language processing
  • Explanations for medical applications
  • Autonomous driving
  • Fairness
  • Causality

Program and Venue

Program

The workshop will contain both keynote talks from known researchers in the field as well as invited talks and spotlight presentations of recent advancements in the field of explainability.

The final program will be announced soon.

Venue

The workshop will take place at the Alte Aula in Tübingen, 28-29th March 2023. Alte Aula is the old auditorium, a historic building whose construction dates back to the 16th century.


Participants will also have the chance to explore the old university town of Tübingen. The city combines the ancient medieval atmosphere with the vibrant life of a cosmopolitan student town. You can get lost in the narrow alleys and timber-framed houses that lead to the 500-years old castle, take a boat trip in the famous "Stocherkahn" or enjoy the tasteful Swabian cuisine. For more information on the city, visit www.tuebingen.de.

Speakers

Trevor Darrell
Trevor Darrell

UC Berkeley

Organizers

Zeynep Akata
Zeynep Akata

Univ. of Tübingen

Stephan Alaniz
Stephan Alaniz

Univ. of Tübingen

Christian Baumgartner
Christian Baumgartner

Univ. of Tübingen

A. Sophia Koepke
A. Sophia Koepke

Univ. of Tübingen

Massimiliano Mancini
Massimiliano Mancini

Univ. of Tübingen

Seong Joon Oh
Seong Joon Oh

Univ. of Tübingen

Workshop funded by the
"Cluster of Excellence -
Machine Learning for Science"
(c) 2021 Explainable Machine Learning Tübingen Impressum