https://github.com/candlelabai/memristorrobustnesstononideality

Code accompanying our manuscript on Enhancing memristor robustness to non-idealities

https://github.com/candlelabai/memristorrobustnesstononideality

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (4.8%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Code accompanying our manuscript on Enhancing memristor robustness to non-idealities

Basic Info
  • Host: GitHub
  • Owner: CandleLabAI
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 1.74 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 1 year ago · Last pushed about 1 year ago
Metadata Files
Readme

README.md

MemristorRobustnessToNonIdeality

Code accompanying our manuscript on Enhancing memristor robustness to non-idealities

  1. There are two folders containing the code for training and testing of three different datastes; FMNIST, NMNIST, and DVS128Gesture.
  2. It takes quite some time to train the netwokrs, therefore each test folder also includes pretrained models. There are a total of 6 trained model files in each folder; one trained in normal way and the other five with different levels of noise.
  3. Please note that testing requires the 'AIHWKIT' installation and this library is only available for linux[1].

[1] https://github.com/IBM/aihwkit

Owner

  • Login: CandleLabAI
  • Kind: user

GitHub Events

Total
  • Delete event: 1
  • Member event: 1
  • Push event: 2
  • Create event: 3
Last Year
  • Delete event: 1
  • Member event: 1
  • Push event: 2
  • Create event: 3