Bayesian neural networks using magnetic tunnel junction-based probabilistic in-memory computing

Bayesian neural networks using magnetic tunnel junction-based probabilistic in-memory computing

Bayesian neural networks (BNNs) combine the generalizability of deep neural networks (DNNs) with a rigorous quantification of predictive uncertainty, which mitigates overfitting and makes them valuable for high-reliability or safety-critical applications. However, the probabilistic nature of BNNs ma...

Full description

Bibliographic Details
Main Authors: Samuel Liu, T. Patrick Xiao, Jaesuk Kwon, Bert J. Debusschere, Sapan Agarwal, Jean Anne C. Incorvia, Christopher H. Bennett
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-10-01
Series:Frontiers in Nanotechnology
Subjects:
spintronics
probabilistic computation
Bayesian inference
neuromorphic computing
domain wall (DW) control
magnetic tunnel junction
Online Access:https://www.frontiersin.org/articles/10.3389/fnano.2022.1021943/full

Internet

https://www.frontiersin.org/articles/10.3389/fnano.2022.1021943/full

Similar Items