The research focus of our lab is on modern machine learning models, in particular deep learning, which is at the core of many recent successes in data science and artificial intelligence. More specifically, we work on the following research topics:

  • (1) Theory of deep learning.
  • (2) Machine learning inspired by natural intelligence and neurobiology.
  • (3) Deep learning for the sciences, with an emphasis on astrophysics.

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Information Theory: A Short Course19.12.2022

This short course on information theory for Bachelor students will introduce fundamental concepts such as entropy, information, sufficiency, typicality, concentration and will present a range of topics from data coding, statistics, inference, decision-making and learning that relate in interesting ways to information theory. It follows the 80-20 rule, trying to focus on relevance and intellectual creativity and leaving out some of the more specialized and technically advanced results. It can be found here in the course catalog.

Carsten Eickhoff joins the Faculty at the University of Tübingen19.12.2022

Carsten Eickhoff, who was a postdoc at DA lab from 2014 - 2017 and one of the founding lab members, has taken up a tenured faculty position at the University of Tübingen as Professor of Medical Data Science. Carsten’s research has been in artificial intelligence for improving patient safety, individual health and quality of medical care. In Tübingen, he will lead the Health NLP Laboratory, specializing in mining, representation and retrieval of large-scale natural language resources. He will remain a visiting researcher at Brown University