From March 23–26, CPAL, the Conference for Parsimony and Learning, brought together researchers from around the world to Tübingen. For several days attendees enjoyed a lively exchange on modern machine learning, with a particular focus on parsimony, structure, and efficiency in learning systems.
Hosted by the ELLIS Institute Tübingen, the Max-Planck-Institute for Intelligent Systems, and the Tübingen AI Center, the conference featured an extensive scientific program including keynote talks, contributed presentations, and poster sessions. Across all formats, CPAL fostered lively discussions and interdisciplinary exchange within the international AI research community.
Over four days, the conference progressed from tutorials on foundational methods and practical techniques to high-level keynotes on feature learning, uncertainty quantification, and institutional machine learning. Renowned speakers from leading international institutions explored how low-dimensional structures can make massive models more efficient and robust.
We are now pleased to share the official event video, offering a look back at some of the highlights and atmosphere of CPAL 2026 in Tübingen.
Special thanks goes to our sponsors HKU Institute of Data Science, CISPA, OPTML, Michigan State University, and all the people who helped make this event possible. Without their support, CPAL would not have been the success it was.
© Video made by Roberto Montebello
Check out our recap and picture gallery of CPAL 2026!