Oct 26, 2017 · Such stochastic devices can provide a direct mapping to the computing elements of Bayesian inference, Deep Belief Networks and probabilistic ...

Jul 15, 2017 · In this work, we experimentally demonstrate a spintronic device that offers a direct mapping to the functionality of such a controllable ...

In this work, we experimentally demonstrate a spintronic device that offers a direct mapping to the functionality of such a controllable stochastic switching ...

Dive into the research topics of 'Stochastic Spin-Orbit Torque Devices as Elements for Bayesian Inference'. Together they form a unique fingerprint. Sort by ...

In this work, we experimentally demonstrate a spintronic device that offers a direct mapping to the functionality of such a controllable stochastic switching ...

Feb 5, 2024 · Consequently, the forward propagation of an SNN with stochastic neurons can be viewed as Bayesian inference. Conversely, in an SNN with ...

Stochastic synapses have also found application in neural sampling machines for approximating Bayesian inference through Monte Carlo sampling [13].

This article proposes an “all-spin” Bayesian neural network where the underlying spintronic hardware provides a better match to the Bayesian computing ...

This work presents an experimental demonstration of a Bayesian network building block implemented with inherently stochastic spintronic devices based on the ...

Jun 11, 2024 · At the hardware level, it calls for devices that can emulate stochastic weight-modification behaviors of synapses with high efficiency. In this ...