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explainable Artificial Intelligence (XAI) aims to bring transparency to today’s powerful but opaque deep learning models. However, the vast majority of current approaches to XAI only provide partial insights and [...] established techniques from XAI can be used to successfully understand, debug and improve machine learning models and pipelines. The session will provide an outlook on how recent developments towards co
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operatedwithout the application of machine learning for safety-critical control components. As it turns out, the specific risk, induced by using machine learning (ML) in safety-critical control systems is [...] Scary or Promising? Machine Learning in Safety-Critical Control Systems One of the Challenges our society faces today has been caused by a recent change of paradigm in computer sciene: the advent of powerful [...] talk, I will focus on a specific "sub-challenge", namely the risks involved in applying machine learning in safety-critical applications and the possibilities to mitigate these risks such that they become
In the last decade, the deep learning community has made considerable progress in the modeling of complex data, in particular with image data. Artificial neural networks are a core building block that [...] illustrate how applied biostatisticians can extend their toolbox with developments from the deep learning community, and also contribute their own perspective.
Schönlieb (U Cambridge): Mathematical imaging: From geometric PDEs and variational modelling to deep learning for images 16:15 Uhr Dusa McDuff (Columbia U): Embedding problems in symplectic topology Für Kaffee
students and young researchers who are interested in the intersection of dynamical systems and machine learning. The participation is free of charge but with prior registration. Please find further information
concerns prediction of a single new instance ("test phase") after a certain number of "training" or "learning" rounds. It is known in this case that under some suitable assumptions on the prediction loss, it [...] consulted each round is limited, or that there is a limited total "expert query budget" for the learning phase. We show that if we are allowed to pick and see the advice of only a single expert per round
Join us as our very own Maria Grandury, herself a Machine Learning Research Engineer, interviews Sandra Hernandez, Systems Engineer at NASA JPL, and Mihaela Popescu, Research Assistant at DFKI (German
discusses topics relevant to both theoretical and practical applications of dynamics, such as machine learning, bifurcation theory, dynamics and geometry, nonlinear waves, computational methods and medicine
buntes Spektrum an Forschungshighlights aus Bremen und "umzu" vor. Co-constructing understanding – learning how to learn from infants as a new approach for teaching robots? Prof. Dr. Britta Wrede Will computers
abstractions, hardware heterogeneity, privacy and security concerns, and big-data driven machine learning models have made the development of optimized AI solutions extremely challenging. This results in