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Decoding finger velocity from cortical spike trains with recurrent spiking neural networks
Tengjun Liu, Julia Gygax, Julian Rossbroich +3
Invasive cortical brain-machine interfaces (BMIs) can significantly improve the life quality of motor-impaired patients. Nonetheless, externally mounted pedestals pose an infection…
Resource-Efficient Speech Quality Prediction through Quantization Aware Training and Binary Activation Maps
Mattias Nilsson, Riccardo Miccini, Clément Laroche +2
As speech processing systems in mobile and edge devices become more commonplace, the demand for unintrusive speech quality monitoring increases. Deep learning methods provide high-…
Theories of synaptic memory consolidation and intelligent plasticity for continual learning
Friedemann Zenke, Axel Laborieux
Humans and animals learn throughout life. Such continual learning is crucial for intelligence. In this chapter, we examine the pivotal role plasticity mechanisms with complex inter…
Elucidating the theoretical underpinnings of surrogate gradient learning in spiking neural networks
Julia Gygax, Friedemann Zenke
Training spiking neural networks to approximate universal functions is essential for studying information processing in the brain and for neuromorphic computing. Yet the binary nat…