Markov Chain Monte Carlo inference on graphical models using event-based processing on the SpiNNaker neuromorphic architecture

D. R. Mendat, Sang Chin, S. Furber, A. G. Andreou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Original languageEnglish
Title of host publicationInformation Sciences and Systems (CISS), 2015 49th Annual Conference on
Pages1-6
Number of pages6
DOIs
Publication statusPublished - 1 Mar 2015

Keywords

  • Markov processes
  • Monte Carlo methods
  • electronic engineering computing
  • hardware-software codesign
  • inference mechanisms
  • neural chips
  • neural net architecture
  • parallel architectures
  • probability
  • sampling methods
  • software architecture
  • Gibb sampling
  • Markov Chain Monte Carlo inference
  • Markov Chain Monte Carlo sampling
  • SpiNNaker neuromorphic architecture
  • brain-inspired energy-aware manner
  • event-based framework
  • event-based processing
  • hardware event-handling capabilities
  • hardware/software architecture
  • massively-parallel neuromorphic hardware architecture
  • neural sampling
  • probabilistic graphical models
  • spiking neurons
  • Bayes methods
  • Computer architecture
  • Graphical models
  • MATLAB
  • Neurons
  • Roads

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