Bayesian Inference on Binary Spiking Networks Leveraging Nanoscale Device Stochasticity
Bayesian Inference on Binary Spiking Networks Leveraging Nanoscale Device Stochasticity
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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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 implementation of random number generators for synaptic...
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Bayesian Inference on Binary Spiking Networks Leveraging Nanoscale Device Stochasticity
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TN_cdi_proquest_journals_2772189887
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2772189887
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E-ISSN
2331-8422
DOI
10.48550/arxiv.2302.01302
