Stochastic sampling via synaptic delay in spiking RBMs using integrated resistive and threshold switching devices | Synapse
June 4, 2026
Stochastic sampling via synaptic delay in spiking RBMs using integrated resistive and threshold switching devices
Key Points
The study aims to explore the role of synaptic delay in facilitating stochastic sampling for enhanced learning in spiking restricted Boltzmann machines.
Implemented a tunable RRAM–TS device for inducing synaptic delay.
Focused on sampling-based learning strategies within spiking restricted Boltzmann machines.
Analyzed the impact of temporal stochasticity on learning efficiency.
The integration of synaptic delay significantly improved sampling efficiency in spiking RBMs.
Demonstrated enhanced learning performance due to increased temporal stochasticity from the device.
Indicated a notable reduction in training time required for effective learning.
Abstract
A tunable RRAM–TS device implements synaptic delay as a source of temporal stochasticity, enabling efficient sampling-based learning in spiking restricted Boltzmann machines.