Bayesian Inference on Binary Spiking Networks Leveraging Nanoscale Device Stochasticity

Bayesian Neural Networks (BNNs) can overcome the problem of overconfidence that plagues traditional frequentist deep neural networks, and are hence considered to be a key enabler for reliable AI systems. However, conventional hardware realizations of BNNs are resource intensive, requiring the implem...

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Veröffentlicht in:	arXiv.org 2023-02
Hauptverfasser:	Katti, Prabodh, Skatchkovsky, Nicolas, Simeone, Osvaldo, Rajendran, Bipin, Al-Hashimi, Bashir M
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Bayesian analysis Computer Science - Emerging Technologies Computer Science - Hardware Architecture Computer Science - Learning Computer Science - Neural and Evolutionary Computing Hardware Memory devices Nanotechnology devices Neural networks Random numbers Sampling Statistical inference Synapses Transistors
Online-Zugang:	Volltext
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