GSI-FAIR Colloquium

More than Moore with Neuromorphic Computing Architectures

by Karlheinz Meier (University of Heidelberg)

Tuesday, December 19, 2017 from to (Europe/Berlin)
at GSI Main Lecture Hall ( SB1 1.120 )
Description
Neuromorphic computing systems represent a departure from the von Neumann architecture. They implement aspects of form and function observed in biological neural circuits. Potential advantages include energy efficiency, fault tolerance, compactness and, most importantly, the ability to learn by interaction with the environment. 

Applications are in two areas : Improving the understanding of biological systems and cognitive computing to analyze causal relations and complex data and to make predictions. In the colloquium I will review current approaches in neuromorphic computing and discuss current and future use cases.


Reading suggestions for the enthusiastic public:

Learning : https://arxiv.org/abs/1604.05080
Mixing : https://arxiv.org/abs/1709.08166
Noise : https://arxiv.org/abs/1710.04931
Dendrites : https://arxiv.org/abs/1703.07286
Some experiments : https://arxiv.org/abs/1703.06043
Sampling : https://arxiv.org/abs/1311.3211

Material:
Organised by Silvia Masciocchi