The research group "Reliable Machine Learning" studies the properties of machine learning algorithms. In view of the recent success of deep learningmethods in applications like image recognition, speech recognition, and automatic translation, the group especially focuses on properties of deep neural networks.
Although a neural network trained e.g. for an image classification task might work well on "real inputs", it has been repeatedly shown empirically that such networks are vulnerable to adversarial examples: a minimal perturbation (impercetible to a human) of the input data can cause the network to misclassify the input. Thus, an important research area of the group is to mathematically understand the reasons for the existence of such adversarial examples (i.e., the instability of trained neural networks), and - building on that understanding - to develop improved methods that yield provably robust neural networks.
Deadline for abstract submissions for EGU Meeting 2024
Prof. Janjic is organizing a session at the upcoming General Assembly of the European Geosciences Union (EGU) in Vienna, Austria,14-19th of April 2024.
The session will be devoted to all aspects of research and development at storm and convective scales and their impact on prediction. A more detailed description of the session Developments in Convective-Scale Data Assimilation, Machine Learning, and Observations is given at https://meetingorganizer.copernicus.org/EGU24/session/48835
Deadline for abstract submissions in January 10th, 2024.
