A Study on In-Memory Binary Neural Networks Using Adiabatic Quantum-Flux-Parametron Logic

Translated title of the contribution: A Study on In-Memory Binary Neural Networks Using Adiabatic Quantum-Flux-Parametron Logic

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Translated title of the contribution	A Study on In-Memory Binary Neural Networks Using Adiabatic Quantum-Flux-Parametron Logic
Original language	Japanese
Pages (from-to)	-
Journal	Proc. 14th Superconducting SFQ VLSI Workshop (SSV 2022)
State	Published - Sep 2022

Cite this

@article{81a6ec2621b24e718c11e06808de29df,

title = "A Study on In-Memory Binary Neural Networks Using Adiabatic Quantum-Flux-Parametron Logic",

author = "\{Tomoharu Yamauchi\} and \{Hao San\} and \{Nobuyuki Yoshikawa\} and \{Olivia Chen\} and Hao SAN",

year = "2022",

month = sep,

language = "Japanese",

pages = "--",

journal = "Proc. 14th Superconducting SFQ VLSI Workshop (SSV 2022)",

}

TY - JOUR

T1 - A Study on In-Memory Binary Neural Networks Using Adiabatic Quantum-Flux-Parametron Logic

AU - Tomoharu Yamauchi, null

AU - Hao San, null

AU - Nobuyuki Yoshikawa, null

AU - Olivia Chen, null

AU - SAN, Hao

PY - 2022/9

Y1 - 2022/9

M3 - 記事

SP - -

JO - Proc. 14th Superconducting SFQ VLSI Workshop (SSV 2022)

JF - Proc. 14th Superconducting SFQ VLSI Workshop (SSV 2022)

ER -