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Neuromorphic Computing


Neuronal networks are capable of processing specific data and tasks optimally and in ‘real time’. Many of these problems are computationally expensive to solve with current computing systems. We thereby develop algorithms and architectures inspired from the design principles of neurobiological networks to solve these problems more efficiently. Example project: Continuous training of recurrent networks.


Research Areas