Cluster Events

Mini-Conference 'Machine Learning in Science', July 22 - 23, 2019

July 22 and 23, 2019 in Tübingen

Details to come soon ...

Symposium 'Machine Learning in Science', May 22, 2019

Symposium 'Machine Learning in Science'

May 22, 2019

Max-Planck-Gästehaus – Lecture Hall (Hörsaal)
Max-Planck-Ring 6, 72076 Tübingen



Tropical circulation: Current challenges and potential for machine learning algorithms
Bedartha Goswami
-- Potsdam Institute for Climate Impact Research (PIK), Germany


High-throughput behavioral analysis for neural circuit understanding
Alexander Mathis
-- Department of Molecular and Cellular Biology, Harvard University, USA


Coffee Break


Reverse Engineering the Early Visual System with Artificial Neural Networks
Stéphane Deny
-- Department of Applied Physics at Stanford University, USA


Visualization of georeferenced open government data: benefits, issues, opportunities for machine learning research
Auriol Degbelo
-- Institute of Geography, University of Osnabrück, Deutschland

Symposium 'Ethics and Philosophy of Machine Learning in Science', May 15, 2019

Symposium 'Ethics and Philosophy of Machine Learning in Science'

May 15, 2019

Max-Planck-Gästehaus – Lecture Hall (Hörsaal)
Max-Planck-Ring 6, 72076 Tübingen



Simplicity and Scientific Progress: A Topological Perspective
Konstantin Genin -- Department of Philosophy, University of Toronto, Canada


Learning Through Creativity
Caterina Moruzzi
-- Department of Philosophy, University of Nottingham, UK


Coffee break


Black-Boxes, Understanding, and Machine Learning
Emily Sullivan-Mumm
-- Ethics and Philosophy of Technology, Delft Data Science, The Netherlands


Working at the margins of machine learning – the ethics of labeling
Thilo Hagendorff
-- International Center for Ethics in the Sciences and Humanities,
University of Tübingen, Germany


Inductive Bias and Adversarial Data
Tom Sterkenburg -- LMU München, Munich Center for Mathematical Philosophy, Germany


Lunch break

13:30 - 14:30

Invited Talk

Co-Opt AI! Charting the emerging field of AI, ethics and social justice

Mona Sloane, Institute for Public Knowledge, New York University, USA

17:10 - 17:55

Conference Room

ML from a DiscO viewpoint: Compressed Sensing, Dictionary Learning and beyond
(machine learning)

Andreas M. Tillmann -- Operations Research & Visual Computing Institute,
RWTH Aachen, Deutschland

Symposium 'Machine Learning in Science', March 18 and 25 - 27, 2019

Symposium „Machine Learning in Science“

March 18 and 25-26, 2018

Max-Planck-Gästehaus – Lecture hall (Hörsaal)
Max-Planck-Ring 6, 72076 Tübingen


Monday, March 18, 2019

09:30 – 10:30

Neutrino Cosmology - Weighing the Ghost Particle with the Universe

   Dr. Elena Giusarma -- Simons Foundation, Flatiron Institute Center for Computational
   Astrophysics, New York, USA


Monday March 25, 2019


Information Field Theory
   PD Dr. Torsten Enßlin -- MPI für Astrophysik, Garching


Active machine learning for automating scientific discovery
   Prof. Dr. Roman Garnett -- Washington University in St. Louis, USA


Coffee break


Bayesian optimisation: nano-machine-learning
   Assoc. Prof. Dr. Michael Osborne -- University of Oxford, UK


Robust and Scalable Learning with Graphs
   Prof. Dr. Stephan Günnemann  -- TU München




Representing and Explaining Novel Concepts with Minimal Supervision

   Asst. Prof. Dr. Zeynep Akata -- University of Amsterdam


Coffee Break


Cluster Member Meeting and General Assembly (non-public)


Joint Dinner (by invitation)


Tuesday, March 26, 2019


Expressive, Robust and Accountable Machine Learning for Real-world Data
   Dr. Isabel Valera -- MPI for Intelligent Systems, Tübingen


Algorithms of Vision: From Brains to Machines and Back
   Dr. Alexander Ecker -- Universität Tübingen


Coffee break


From Paired to Unpaired Image-to-Image Translation and Beyond
   Dr. Radu Timofte -- ETH Zürich, Schweiz


Face processing: Bridging Natural and Artificial Intelligence

   Assoc. Prof. Dr. Angela J. Yu -- University of California San Diego, USA



14:00 From statistics to mechanisms, and back
   Prof. Dr. Jakob Macke -- TU München


Machine Learning meets Law, March 19, 2019

Machine Learning meets Law, Neue Aula

9:00 Stefan Thomas: Algorithms and Antitrust: How can the law make sure that machine learning does not impede competitive freedom?

9:15 Thilo Hagendorff: Regularory Needs in the Field of AI - From Ethics to Policies

9:30 Thomas Grote: The ethics of (expert-level) algorithmic decision-making

9:45 Isabel Valera: Fairness in Machine Learning

10:00 Oliver Kohlbacher: Legal issues related to AI in medicine

10:15 Discussion as long as we want

Meeting of the Cluster 'Machine Learning in Science', November 12-13, 2018

Internal Meeting of the Cluster "Machine Learning in Science": November 12-13, 2018

Meeting location: Ground floor lecture hall at the Max-Planck Institute for Intelligent Systems (directions)

Preliminary schedule:

Nov 12th
9:00-10:00   Welcome, information & organisation
                     Ulrike von Luxburg and Philipp Berens
10:00-12:15   Short introductory talks of new group leaders
10:00-10:15   Jörg Stückler
10:15-10:30   Falk Lieder

10:30-11:00   Coffee break

11:00-11:15   Georg Martius
11:15-11:30   Britta Dorn
11:30-11:45   Fabian Sinz
11:45-12:00   Zhaoping Li
12:00-12:15   Gabriele Schweikert
12:15-12:30   Augustin Kelava
12:30-12:45   Michael Krone

12.45 -14:00   Lunch

14:00-15:00   Spotlights for open questions
                       (all PIs: please prepare exactly 1 slide (3 minutes) and send it to Alla at latest Nov 11)
15:00-15:30   Coffee break
15:30-18:00   Work phase for project teams

18:30   Dinner at Hofgut Rosenau

Nov 13th
9:00-10:30   Discussion of open questions, directions, ideas for how
                     the Excellence Cluster should start and work

10:30-11:00   Coffee break

11:00-12:00   Discussion and work phase

12:00-14:00   Lunch

14:00-15:00   Presentations of project ideas and discussion

15:00-15:30   Coffee break

Download program