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Category:
Life Science

Lecturer:
Carsten Rother, Visual Learning Lab, Heidelberg

Place:
HITS, Carl-Bosch-Auditorium of Studio Villa Bosch, Schloss-Wolfsbrunnenweg 33

Host:
HITS

Description:
In this talk I will introduce the Visual Learning Lab Heidelberg. We conduct basic research in the fields of machine learning and combinatorial optimization with application to image analysis, microscopy, astrophysics, medicine, and other fields in Natural- and Life sciences. In this talk, I will present a collection of our research projects. One of the projects is to solve inverse problems with a new form of so-called invertible neural networks, which allows a bijective mapping between parameter-space and measurement-space. The beauty of this approach is that a full distribution of the parameter-space can be reconstructed without any assumptions about its shape. Another project shows how we can learn to generate synthetic labeled data that can be used as a proxy for real-world annotated data, which is often lacking in practical scenarios. A final project demonstrates how to combine neural networks with classical sampling-based algorithms in order to achieve improved task-specific performance.

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