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Binary-Stochasticity-Enabled Highly Efficient Neuromorphic Deep Learning Achieves Better-than-Software Accuracy.

Y. Li, W. Wang, M. Wang, C. Dou, Z. Ma, H. Zhou, P. Zhang, N. Lepri, X. Zhang, Q. Luo, X. Xu, G. Yang, F. Zhang, L. Li, D. Ielmini, and M. Liu. Adv. Intell. Syst., (January 2024)

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Bruno Lepri

Uwe Leprich

Audrey Leprince

Uwe Leprich

Nicola Gess

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Binary stochasticity enabled highly efficient neuromorphic deep learning achieves better-than-software accuracy.Y. Li, W. Wang, M. Wang, C. Dou, Z. Ma, H. Zhou, P. Zhang, N. Lepri, X. Zhang, Q. Luo and 6 other author(s). CoRR, (2023)NimbleAI: Towards Neuromorphic Sensing-Processing 3D-integrated Chips.X. Iturbe, N. Abderrahmane, J. Abella, S. Alcaide, E. Beyne, H. Charles, C. Charpin-Nicolle, L. Chittka, A. Dávila, A. Erdmann and 39 other author(s). DATE, page 1-6. IEEE, (2023)Binary-Stochasticity-Enabled Highly Efficient Neuromorphic Deep Learning Achieves Better-than-Software Accuracy.Y. Li, W. Wang, M. Wang, C. Dou, Z. Ma, H. Zhou, P. Zhang, N. Lepri, X. Zhang, Q. Luo and 6 other author(s). Adv. Intell. Syst., (January 2024)Enhancing reliability of a strong physical unclonable function (PUF) solution based on virgin-state phase change memory (PCM).L. Cattaneo, M. Baldo, N. Lepri, F. Sancandi, M. Borghi, E. Petroni, A. Serafini, R. Annunziata, A. Redaelli, and D. Ielmini. IRPS, page 1-6. IEEE, (2023)Mitigating read-program variation and IR drop by circuit architecture in RRAM-based neural network accelerators.N. Lepri, A. Glukhov, and D. Ielmini. IRPS, page 3. IEEE, (2022)End-to-end modeling of variability-aware neural networks based on resistive-switching memory arrays.A. Glukhov, N. Lepri, V. Milo, A. Baroni, C. Zambelli, P. Olivo, E. Pérez, C. Wenger, and D. Ielmini. VLSI-SoC, page 1-5. IEEE, (2022)Statistical model of program/verify algorithms in resistive-switching memories for in-memory neural network accelerators.A. Glukhov, V. Milo, A. Baroni, N. Lepri, C. Zambelli, P. Olivo, E. Pérez, C. Wenger, and D. Ielmini. IRPS, page 3. IEEE, (2022)In-memory neural network accelerator based on phase change memory (PCM) with one-selector/one-resistor (1S1R) structure operated in the subthreshold regime.N. Lepri, P. Gibertini, P. Mannocci, A. Pirovano, I. Tortorelli, P. Fantini, and D. Ielmini. IMW, page 1-4. IEEE, (2023)

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Binary-Stochasticity-Enabled Highly Efficient Neuromorphic Deep Learning Achieves Better-than-Software Accuracy.

Please choose a person to relate this publication to

Bruno Lepri

Uwe Leprich

Audrey Leprince

Uwe Leprich

Nicola Gess

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Lepri, Nicola"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Binary-Stochasticity-Enabled Highly Efficient Neuromorphic Deep Learning Achieves Better-than-Software Accuracy.

Please choose a person to relate this publication to

Bruno Lepri

Uwe Leprich

Audrey Leprince

Uwe Leprich

Nicola Gess

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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history of this post
URL
DOI
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APA
Chicago
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Binary-Stochasticity-Enabled Highly Efficient Neuromorphic Deep Learning Achieves Better-than-Software Accuracy.