Speaker
Dr
Ramsés Sanchéz
(Lamarr institute, University of Bonn)
Description
Researchers at Hybrid-ML tackle a wide range of applied and theoretical problems, characterized by different data modalities, such as time series, graphs, natural language, images, and their combinations. Solving these problems requires drawing from an equally broad spectrum of background knowledge, from abstract algebra and statistical physics to cognitive psychology. Yet, despite this diversity, many of our target problems share common underlying concepts and structures. At Hybrid-ML, we should recognize and leverage this common structure to our advantage.
This discussion session will focus on only one question: How can we do this — viz. To recognize and leverage these concepts and structures— effectively and precisely?
