Search Results for author: Martin Lueker-Boden

Found 4 papers, 0 papers with code

Layer Ensemble Averaging for Improving Memristor-Based Artificial Neural Network Performance

no code implementations24 Apr 2024 Osama Yousuf, Brian Hoskins, Karthick Ramu, Mitchell Fream, William A. Borders, Advait Madhavan, Matthew W. Daniels, Andrew Dienstfrey, Jabez J. McClelland, Martin Lueker-Boden, Gina C. Adam

Results demonstrate that by trading off the number of devices required for layer mapping, layer ensemble averaging can reliably boost defective memristive network performance up to the software baseline.

Continual Learning

Measurement-driven neural-network training for integrated magnetic tunnel junction arrays

no code implementations11 Dec 2023 William A. Borders, Advait Madhavan, Matthew W. Daniels, Vasileia Georgiou, Martin Lueker-Boden, Tiffany S. Santos, Patrick M. Braganca, Mark D. Stiles, Jabez J. McClelland, Brian D. Hoskins

Methods such as hardware-aware training, where substrate non-idealities are incorporated during network training, are one way to recover performance at the cost of solution generality.

Device Modeling Bias in ReRAM-based Neural Network Simulations

no code implementations29 Nov 2022 Osama Yousuf, Imtiaz Hossen, Matthew W. Daniels, Martin Lueker-Boden, Andrew Dienstfrey, Gina C. Adam

Data-driven modeling approaches such as jump tables are promising techniques to model populations of resistive random-access memory (ReRAM) or other emerging memory devices for hardware neural network simulations.


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