| Accurate program/verify schemes of resistive switching memory (RRAM) for in-memory neural network circuits V Milo, A Glukhov, E Pérez, C Zambelli, N Lepri, MK Mahadevaiah, ... IEEE Transactions on Electron Devices 68 (8), 3832-3837, 2021 | 89 | 2021 |
| In-memory computing with emerging memory devices: Status and outlook P Mannocci, M Farronato, N Lepri, L Cattaneo, A Glukhov, Z Sun, ... APL Machine Learning 1 (1), 2023 | 75 | 2023 |
| Modeling and compensation of IR drop in crosspoint accelerators of neural networks N Lepri, M Baldo, P Mannocci, A Glukhov, V Milo, D Ielmini IEEE Transactions on Electron Devices 69 (3), 1575-1581, 2022 | 27 | 2022 |
| In-memory computing for machine learning and deep learning N Lepri, A Glukhov, L Cattaneo, M Farronato, P Mannocci, D Ielmini IEEE Journal of the Electron Devices Society 11, 587-601, 2023 | 18 | 2023 |
| Mitigating read-program variation and IR drop by circuit architecture in RRAM-based neural network accelerators N Lepri, A Glukhov, D Ielmini 2022 IEEE International Reliability Physics Symposium (IRPS), 3C. 2-1-3C. 2-6, 2022 | 9 | 2022 |
| Nimbleai: Towards neuromorphic sensing-processing 3d-integrated chips X Iturbe, N Abderrahmane, J Abella, S Alcaide, E Beyne, HP Charles, ... 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE), 1-6, 2023 | 6 | 2023 |
| 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, ... 2022 IEEE International Reliability Physics Symposium (IRPS), 3C. 3-1-3C. 3-7, 2022 | 6 | 2022 |
| Status and challenges of in-memory computing for neural accelerators D Ielmini, N Lepri, P Mannocci, A Glukhov 2022 International Symposium on VLSI Technology, Systems and Applications …, 2022 | 5 | 2022 |
| 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, ... Advanced Intelligent Systems 6 (1), 2300399, 2024 | 3 | 2024 |
| 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, ... 2022 IFIP/IEEE 30th International Conference on Very Large Scale Integration …, 2022 | 3 | 2022 |
| Compact modeling and mitigation of parasitics in crosspoint accelerators of neural networks N Lepri, A Glukhov, P Mannocci, M Porzani, D Ielmini IEEE Transactions on Electron Devices, 2024 | 2 | 2024 |
| 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, ... 2023 IEEE International Memory Workshop (IMW), 1-4, 2023 | 2 | 2023 |
| 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, ... 2023 IEEE International Reliability Physics Symposium (IRPS), 1-6, 2023 | 1 | 2023 |
| Low-energy, high-accuracy convolutional network inference in 3D crosspoint (3DXP) arrays F Carletti, M Farronato, N Lepri, I Tortorelli, A Pirovano, P Fantini, ... 2024 IEEE European Solid-State Electronics Research Conference (ESSERC), 412-415, 2024 | | 2024 |
| In-memory analog acceleration of Deep Learning inference N Lepri | | 2023 |
| Cross-point memory arrays: selection devices and circuit simulation N Lepri politesi.polimi.it, 2020 | | 2020 |
| RECENT PROGRESSES OF IN-MEMORY COMPUTING: MATERIALS, DEVICES AND ARCHITECTURES D Ielmini, F Sancandi, M Farronato, S Hashemkhani, S Ricci, M Baldo, ... BOOK OF ABSTRACTS, 23, 0 | | |
