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Explores the learning dynamics of deep neural networks using linear networks for analysis, covering two-layer and multi-layer networks, self-supervised learning, and benefits of decoupled initialization.
Discusses the challenges and future of neuromorphic computing, comparing digital computers and specialized hardware, such as SpiNNaker and NEST, while exploring the Human Brain Project's Neuromorphic Computing Platform.
