Uncertainty Qualification in Biomedical Imaging
We are happy to welcome the next round of our AI paper reading group, where we will cover AI-related papers to keep up to date with what is happening in this fast-moving environment.
In this edition of the Paper Reading Group, we welcome Tim Adler, a final-year Ph.D. student and data scientist at DKFZ (German Cancer Research Center). Machine learning (ML) and deep learning, in particular, have led to leaps in many computer science and real-world problems.
Therefore, it is no surprise that ML has also entered the medical domain. However, breakthroughs and success stories are still lacking. One main reason lies in the strict safety requirements of the field. In this talk, Tim will present recent work on uncertainty quantification, which tries to teach ML models “to know what they do not know”
Register below to attend in person at the AI Campus Berlin, or join online