A Tensor Train decomposition-based method enables efficient gradient-free activation maximization for neurons in spiking neural networks by searching generative model latent spaces.
Simple model of spiking neurons,
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A literature survey of FPGA-based digital neuromorphic architectures over 25 years that creates a taxonomy of architectural features, lists advantages and disadvantages, and identifies trends.
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Fast gradient-free activation maximization for neurons in spiking neural networks
A Tensor Train decomposition-based method enables efficient gradient-free activation maximization for neurons in spiking neural networks by searching generative model latent spaces.
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A Quarter of a Century of Neuromorphic Architectures on FPGAs -- an Overview
A literature survey of FPGA-based digital neuromorphic architectures over 25 years that creates a taxonomy of architectural features, lists advantages and disadvantages, and identifies trends.