A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is
This paper discusses biologically inspired machine learning methods based on theories about how the brain exploits noise to carry out computations, such as probabilistic inference through sampling. ABSTRACT | We are used to viewing noise as a nuisance in computing systems. This is a pity, since noise will be abundantly available in energy-efficient future nanoscale devices and circuits. I propose here to learn from the way the brain deals with noise, and apparently even benefits from it. Recentdoi:10.1109/jproc.2014.2310593 fatcat:54mgt3scqje5flvjqnad45okfi