Demonstrates efficient sampling-based learning in spiking restricted Boltzmann machines using tunable devices, indicating significant implications for neural computation.
A tunable RRAM–TS device implements synaptic delay as a source of temporal stochasticity, enabling efficient sampling-based learning in spiking restricted Boltzmann machines.
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Jang et al. (2026) studied this question.
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