Energy-efficient continual learning in hybrid supervised-unsupervised neural networks with PCM synapses. - Stefano Bianchi; I. Muñoz-Martín; Giacomo Pedretti; Octavian Melnic; Stefano Ambrogio; Daniele Ielmini (VLSI Circuits, 2019)

A Bio-Inspired Recurrent Neural Network with Self-Adaptive Neurons and PCM Synapses for Solving Reinforcement Learning Tasks. - Stefano Bianchi; I. Muñoz-Martín; S. Hashemkhani; Giacomo Pedretti; Daniele Ielmini (ISCAS, 2020)

Hardware Implementation of PCM-Based Neurons with Self-Regulating Threshold for Homeostatic Scaling in Unsupervised Learning. - I. Muñoz-Martín; Stefano Bianchi; S. Hashemkhani; Giacomo Pedretti; Daniele Ielmini (ISCAS, 2020)

Drift Compensation in Multilevel PCM for in-Memory Computing Accelerators. - L. Pistolesi; Artem Glukhov; Amadeo de Gracia Herranz; Marisa López-Vallejo; Marcella Carissimi; Marco Pasotti; Pier Luigi Rolandi; Andrea Redaelli; I. Muñoz-Martín; S. Bianchi; Andrea Bonfanti; Daniele Ielmini (IRPS, 2024)