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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
Section: Fachbereich 03
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
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