Tommaso Stecconi

Filamentary TaO_<i>x</i>/HfO₂ ReRAM Devices for Neural Networks Training with Analog In‐Memory Computing

Tommaso Stecconi, Roberto Guido, Luca Berchialla et al. · Advanced Electronic Materials · 2022 · 39 citations · Full text

Engineering, Computer Engineering, Materials Science +14

A Volatile RRAM Synapse for Neuromorphic Computing

Erika Covi, Yu‐Hsuan Lin, Wei Wang et al. · 2019 · 29 citations

Life Sciences, Electrical Engineering, Materials Science +16

Analog Resistive Switching Devices for Training Deep Neural Networks with the Novel Tiki-Taka Algorithm

Tommaso Stecconi, Valeria Bragaglia, Malte J. Rasch et al. · Nano Letters · 2024 · 19 citations · Full text

Engineering, Computer Engineering, Electrical Engineering +17

Analytical modelling of the transport in analog filamentary conductive-metal-oxide/HfO_x ReRAM devices

Donato Francesco Falcone, Stephan Menzel, Tommaso Stecconi et al. · Nanoscale Horizons · 2024 · 13 citations · Full text

Engineering, Electrical Engineering, Materials Science +16

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfO_x ReRAM Devices

Donato Francesco Falcone, Victoria Clerico, Wooseok Choi et al. · Advanced Functional Materials · 2025 · 12 citations · Full text

Engineering, Computer Engineering, Electrical Engineering +17