Statistical model of program/verify algorithms in resistive-switching memories for in-memory neural network accelerators. - Artem Glukhov; Valerio Milo; Andrea Baroni; Nicola Lepri; Cristian Zambelli; Piero Olivo; Eduardo Pérez; Christian Wenger; Daniele Ielmini (IRPS, 2022)

Mitigating read-program variation and IR drop by circuit architecture in RRAM-based neural network accelerators. - Nicola Lepri; Artem Glukhov; Daniele Ielmini (IRPS, 2022)

End-to-end modeling of variability-aware neural networks based on resistive-switching memory arrays. - Artem Glukhov; Nicola Lepri; Valerio Milo; Andrea Baroni; Cristian Zambelli; Piero Olivo; Eduardo Pérez; Christian Wenger; Daniele Ielmini (VLSI-SoC, 2022)

NimbleAI: Towards Neuromorphic Sensing-Processing 3D-integrated Chips. - Xabier Iturbe; Nassim Abderrahmane; Jaume Abella 001; Sergi Alcaide; Eric Beyne; Henri-Pierre Charles; Christelle Charpin-Nicolle; Lars Chittka; Angélica Dávila; Arne Erdmann; Carles Estrada; Ander Fernández; et al. (DATE, 2023)

In-memory neural network accelerator based on phase change memory (PCM) with one-selector/one-resistor (1S1R) structure operated in the subthreshold regime. - Nicola Lepri; P. Gibertini; Piergiulio Mannocci; A. Pirovano; I. Tortorelli; Paolo Fantini; Daniele Ielmini (IMW, 2023)

Enhancing reliability of a strong physical unclonable function (PUF) solution based on virgin-state phase change memory (PCM). - L. Cattaneo; Matteo Baldo; Nicola Lepri; Flavio Sancandi; Massimo Borghi; Elisa Petroni; A. Serafini; Roberto Annunziata; Andrea Redaelli; Daniele Ielmini (IRPS, 2023)

Binary-Stochasticity-Enabled Highly Efficient Neuromorphic Deep Learning Achieves Better-than-Software Accuracy. - Yang Li 203; Wei Wang 209; Ming Wang; Chunmeng Dou; Zhengyu Ma; Huihui Zhou; Peng Zhang 077; Nicola Lepri; Xumeng Zhang; Qing Luo; Xiaoxin Xu; Guanhua Yang; et al. (Adv. Intell. Syst., 2024)