BIANCHI, STEFANO

BIANCHI, STEFANO  

DIPARTIMENTO DI ELETTRONICA, INFORMAZIONE E BIOINGEGNERIA  

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Titolo Data di pubblicazione Autori File
A bio-inspired recurrent neural network with self-adaptive neurons and PCM synapses for solving reinforcement learning tasks 1-gen-2020 S. BianchiI. Muñoz MartínS. HashemkhaniG. PedrettiD. Ielmini
A Brain-Inspired Homeostatic Neuron Based on Phase-Change Memories for Efficient Neuromorphic Computing 1-gen-2021 Bianchi S.Hashemkhani S.Pedretti G.Melnic O.Ielmini D. +
A Compact Model for Stochastic Spike-Timing-Dependent Plasticity (STDP) Based on Resistive Switching Memory (RRAM) Synapses 1-gen-2020 Bianchi, StefanoPedretti, GiacomoMunoz-Martin, IreneIelmini, Daniele +
A Drift-Resilient Hardware Implementation of Neural Accelerators Based on Phase Change Memory Devices 1-gen-2021 Bianchi S.Melnic O.Bonfanti A. G.Ielmini D. +
A Multilayer Neural Accelerator With Binary Activations Based on Phase-Change Memory 1-gen-2023 Bertuletti, MarcoBianchi, StefanoBonfanti, Andrea G.Ielmini, Daniele +
A self-adaptive hardware with resistive switching synapses for experience-based neurocomputing 1-gen-2023 Bianchi, SCovi, EBricalli, AIelmini, D +
A SiOx RRAM-based hardware with spike frequency adaptation for power-saving continual learning in convolutional neural networks 1-gen-2020 I. Muñoz MartínS. BianchiE. CoviA. BricalliD. ielmini +
Bio-Inspired Techniques in a Fully Digital Approach for Lifelong Learning 1-gen-2020 Bianchi S.MUÑOZ MARTÍN IRENEIelmini D.
Combining accuracy and plasticity in convolutional neural networks based on resistive memory arrays for autonomous learning 1-gen-2021 Bianchi S.Covi E.Bricalli A.Ielmini D. +
Differential Phase Change Memory (PCM) Cell for Drift-Compensated In-Memory Computing 1-gen-2024 L. PistolesiL. RavelliA. GlukhovI. Muñoz MartínS. BianchiA. BonfantiD. Ielmini +
Energy-efficient continual learning in hybrid supervised-unsupervised neural networks with PCM synapses 1-gen-2019 Bianchi S.Munoz-Martin I.Pedretti G.Melnic O.Ambrogio S.Ielmini D.
Hardware implementation of PCM-based neurons with self-regulating threshold for homeostatic scaling in unsupervised learning 1-gen-2020 I. Muñoz MartínS. BianchiS. HashemkhaniG. PedrettiD. Ielmini
Memristive neural network for on-line learning and tracking with brain-inspired spike timing dependent plasticity 1-gen-2017 Pedretti, G.Milo, V.Ambrogio, S.Carboni, R.Bianchi, S.Sottocornola Spinelli, A.Ielmini, D. +
Modeling-based design of brain-inspired spiking neural networks with RRAM learning synapses 1-gen-2017 Pedretti, G.Bianchi, S.Milo, V.Ielmini, D. +
Resistive switching synapses for unsupervised learning in feed-forward and recurrent neural networks 1-gen-2018 MILO, VALERIOPEDRETTI, GIACOMOLaudato, M.BRICALLI, ALESSANDROAMBROSI, ELIABIANCHI, STEFANOCHICCA, ELISABETTAIelmini, D.
Stochastic Learning in Neuromorphic Hardware via Spike Timing Dependent Plasticity with RRAM Synapses 1-gen-2018 Pedretti, GiacomoMilo, ValerioAmbrogio, StefanoCARBONI, ROBERTOBIANCHI, STEFANOSpinelli, Alessandro S.Ielmini, Daniele +
Unsupervised Learning to Overcome Catastrophic Forgetting in Neural Networks 1-gen-2019 Munoz-Martin I.Bianchi S.Pedretti G.Melnic O.Ambrogio S.Ielmini D.