publications

2025

1. Nature

   Layer ensemble averaging for fault tolerance in memristive neural networks

   Osama Yousuf, Brian D Hoskins, Karthick Ramu, Mitchell Fream, and 7 more authors

   Nature Communications, 2025

   DOI Bib

   

   @article{yousuf2025layer,
     title = {Layer ensemble averaging for fault tolerance in memristive neural networks},
     author = {Yousuf, Osama and Hoskins, Brian D and Ramu, Karthick and Fream, Mitchell and Borders, William A and Madhavan, Advait and Daniels, Matthew W and Dienstfrey, Andrew and McClelland, Jabez J and Lueker-Boden, Martin and others},
     journal = {Nature Communications},
     volume = {16},
     number = {1},
     pages = {1250},
     year = {2025},
     publisher = {Nature Publishing Group UK London},
     doi = {10.1038/s41467-025-56319-6},
     url = {https://www.nature.com/articles/s41467-025-56319-6},
     dimensions = {true},
   }

2023

1. NANOARCH

   Neural Network Modeling Bias for Hafnia-based FeFETs

   Osama Yousuf, Imtiaz Hossen, Andreu Glasmann, Sina Najmaei, and 1 more author

   In Proceedings of the 18th ACM International Symposium on Nanoscale Architectures, 2023

   DOI Bib

   

   @inproceedings{yousuf2023neural,
     title = {Neural Network Modeling Bias for Hafnia-based FeFETs},
     author = {Yousuf, Osama and Hossen, Imtiaz and Glasmann, Andreu and Najmaei, Sina and Adam, Gina C},
     booktitle = {Proceedings of the 18th ACM International Symposium on Nanoscale Architectures},
     pages = {1--5},
     year = {2023},
     doi = {10.1145/3611315.3633253},
     url = {https://dl.acm.org/doi/abs/10.1145/3611315.3633253},
     dimensions = {true},
   }

2. JETCAS

   Device Modeling Bias in ReRAM-based Neural Network Simulations

   Osama Yousuf, Imtiaz Hossen, Matthew W Daniels, Martin Lueker-Boden, and 2 more authors

   IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2023

   DOI Bib

   

   @article{yousuf2023device,
     title = {Device Modeling Bias in ReRAM-based Neural Network Simulations},
     author = {Yousuf, Osama and Hossen, Imtiaz and Daniels, Matthew W and Lueker-Boden, Martin and Dienstfrey, Andrew and Adam, Gina C},
     journal = {IEEE Journal on Emerging and Selected Topics in Circuits and Systems},
     volume = {13},
     number = {1},
     pages = {382--394},
     year = {2023},
     publisher = {IEEE},
     doi = {10.1109/JETCAS.2023.3238295},
     url = {https://ieeexplore.ieee.org/abstract/document/10024104},
     dimensions = {true},
   }

2021

1. Frontiers

   Gradient decomposition methods for training neural networks with non-ideal synaptic devices

   Junyun Zhao, Siyuan Huang, Osama Yousuf, Yutong Gao, and 2 more authors

   Frontiers in Neuroscience, 2021

   DOI Bib

   

   @article{zhao2021gradient,
     title = {Gradient decomposition methods for training neural networks with non-ideal synaptic devices},
     author = {Zhao, Junyun and Huang, Siyuan and Yousuf, Osama and Gao, Yutong and Hoskins, Brian D and Adam, Gina C},
     journal = {Frontiers in Neuroscience},
     volume = {15},
     pages = {749811},
     year = {2021},
     publisher = {Frontiers Media SA},
     doi = {10.3389/fnins.2021.749811},
     url = {https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2021.749811/full},
     dimensions = {true},
   }

2. ICONS

   A system for validating resistive neural network prototypes

   Brian Hoskins, Wen Ma, Mitchell Fream, Osama Yousuf, and 7 more authors

   In International Conference on Neuromorphic Systems 2021, 2021

   DOI Bib

   

   @inproceedings{hoskins2021system,
     title = {A system for validating resistive neural network prototypes},
     author = {Hoskins, Brian and Ma, Wen and Fream, Mitchell and Yousuf, Osama and Daniels, Mathew and Goodwill, Jonathan and Madhavan, Advait and Tung, Hoang and Branstad, Mark and Liu, Muqing and others},
     booktitle = {International Conference on Neuromorphic Systems 2021},
     pages = {1--5},
     year = {2021},
     doi = {10.1145/3477145.3477260},
     url = {https://dl.acm.org/doi/abs/10.1145/3477145.3477260},
     dimensions = {true},
   }