14 citations · 32 across the 7 of their papers we have counts for
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cs.ET2026★ 4 cited
Update Disturbance-Resilient Analog ReRAM Crossbar Arrays for In-Memory Deep Learning Accelerators
Wooseok Choi, Tommaso Stecconi, Donato Francesco Falcone +14
Resistive memory (ReRAM) technologies with crossbar array architectures hold significant potential for analog AI accelerator hardware, enabling both in-memory inference and trainin…
cs.ET2026★ 1 cited
Study of Resistive Switching Dynamics and Memory States Equilibria in Analog Filamentary Conductive-Metal-Oxide/HfOx ReRAM via Compact Modeling
Matteo Galetta, Donato Francesco Falcone, Victoria Clerico +7
Resistive Random Access Memory (ReRAM) devices offer a promising solution for next-generation non-volatile memory and neuromorphic computing systems. Yet, existing compact models f…