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Peter Grünberg Institute (PGI)

Neuromorphic Software Ecosystems (PGI-15)

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    • Surrogate Gradient Learning and local learning
      • Neuromorphic machine learning software design and novel autodifferentiation techniques for training spiking neural networks
        • Designing Memristive Neuromorphic Learning Machines for Fast, Real-Time Adaptation
          • Meta-learning (Learning-to-learn)
            • Cloud-to-Edge Physics-Informed Neural Networks
              • Neuromorphic Hardware for Approximate Bayesian Inference and Optimization
                • Neuromorphic Applications in Vision and Robotics
                  • Neural Code Agnostic Methods for Comparing Brains and Artificial Neural Networks
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                              Neuromorphic Software Ecosystems (PGI-15)

                              We create neuromorphic computing technologies that learn and work like the brain by designing computer algorithms and computing architectures from the perspective of neuroscience and realization of dedicated circuits and devices.

                              Director: Prof. Emre Neftci

                              If one was given a box containing a billion neurons and a trillion wires to connect them together, how should one proceed to build an intelligent system?

                              The Peter Grünberg Institute 15 - Neuromorphic Software Ecosystem (PGI-15) explores answers to this question by creating neuromorphic computing technologies that learn and work like the brain. To achieve this, our research team redesigns computer algorithms and computing architectures from the perspective of Neuroscience and its physical realization in dedicated circuits and devices. Applications of our research are poised to improve computer vision algorithms for autonomous control, data processing in mobile and wearable devices, and to scale up scientific data analysis. PGI-15 is led by Prof. Dr. Neftci.

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