Machine Learning and Brain Research are closely related: artificial neural networks were inspired by biology, and neuroscience is using machine learning to understand the brain. Marco Lehmann will start with an overview of the fascinating world of brain research and then explore the intersection of the two fields. By covering a few key results from theoretical neuroscience and from machine learning he will point out similarities and differences between the brain and current computers. The talk will be complemented by two short perspectives: First, Alex Seeholzer will speak about the intersection of big data and neuronal models, and how this helps biologists understand their data. Then, Johanni Brea will report about the deep learning revolution and current challenges in machine learning.
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