Neuro-inspired Theory, Modeling and Applications
Our theoretical research is concerned with understanding and analytically describing various aspects of neural network dynamics. On the modeling side, we are mainly interested in functional networks (i.e., networks that do something that we consider useful), for which we take inspiration from both biology and AI research. An essential aspect of model functionality concerns robustness, since one of our goals is the embedding of functional networks in neuromorphic substrates and their application to real-world problems.
Our Research Interests
Listen to the podcast "The intersection of biological and artificial intelligence"
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DEEP MINDS Podcast (in German) - Info
eLife Article: how natural-gradient descent enable efficient synaptic plasticity!
"Natural-gradient learning for spiking neurons".
Our group leader speaks his mind!