Covariant spatio-temporal receptive fields for spiking neural networks

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Neuromorphic computing exploits the laws of physics to perform computations, similar to the human brain. If we can “lower” the computation into physics, we achieve extreme energy gains, up to 27-35 orders of magnitude. So, why aren’t we doing that? Presently, we lack theories to guide efficient implementations. We can build the circuits, but we don’t know how to combine…

Read on /posts/202510_nrf/ ↗