Skip to main content
King Abdullah University of Science and Technology
Scientific Computing and Machine Learning
SCML
Bayesian Deep Learning

Main navigation

  • Home
  • People
    • All Profiles
    • Principal Investigators
    • Postdoctoral Fellows
  • Events
    • All Events
    • Events Calendar
  • News
  • Software
  • Projects
  • Topics
  • Courses
  • Theses
  • Publications

Spiking Neurons

Memristors Empower Spiking Neurons With Stochasticity

1 min read · Sun, Apr 26 2015

News

Circuits Spiking Neurons Stochasticity memristors

Maruan Al-Shedivat, et al., "Memristors empower spiking neurons with stochasticity." IEEE journal on Emerging and Selected Topics in Circuits and Systems 5 (2), 2015, 242. Abstract: Recent theoretical studies have shown that probabilistic spiking can be interpreted as learning and inference in cortical microcircuits. This interpretation creates new opportunities for building neuromorphic systems driven by probabilistic learning algorithms. However, such systems must have two crucial features: 1) the neurons should follow a specific behavioral model, and 2) stochastic spiking should be

Bayesian Deep Learning (BDL)

Footer

  • A-Z Directory
    • All Content
    • Browse Related Sites
  • Site Management
    • Log in

© 2025 King Abdullah University of Science and Technology. All rights reserved. Privacy Notice