27.03.2025
Beyond the Black Box: Choosing the Right Feature Importance Method
MCML Research Insight - With Fiona Katharina Ewald, Ludwig Bothmann, Giuseppe Casalicchio and Bernd Bischl
Machine learning models make powerful predictions, but can we really trust them if we don’t understand how they work? Global feature importance methods help us discover which factors really matter - but choosing the wrong method can lead to misleading conclusions. To see why this is important, …
©TUM
24.03.2025
Azade Farshad Receives BVM Award for Top Medical Imaging Research
Our junior member Azade Farshad was awarded the BVM Award for the best thesis in medical image processing. Her work, supervised by Nassir Navab, was recognized for its innovation and excellence. The award was presented at the German Conference on Medical Image Computing (BVM), held at OTH Regensburg. …
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21.03.2025
Explainable Multimodal Agents With Symbolic Representations & Can AI Be Less Biased?
Our Junior Member Ruotong Liao at United Nations AI for Good
More than 170 audiences visited the online lecture of our Junior Member Ruotong Liao on Monday, 17. March 2025, as an invited speaker at the United Nations “AI for Good”. With her talk “Perceive, Remember, and Predict: Explainable Multimodal Agents with Symbolic Representations,” Ruotong Liao took …