Підписатись
Valerio Milo
Valerio Milo
Applied Materials
Підтверджена електронна адреса в amat.com
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Learning of spatiotemporal patterns in a spiking neural network with resistive switching synapses
W Wang, G Pedretti, V Milo, R Carboni, A Calderoni, N Ramaswamy, ...
Science advances 4 (9), eaat4752, 2018
2672018
Neuromorphic learning and recognition with one-transistor-one-resistor synapses and bistable metal oxide RRAM
S Ambrogio, S Balatti, V Milo, R Carboni, ZQ Wang, A Calderoni, ...
IEEE Transactions on Electron Devices 63 (4), 1508-1515, 2016
2562016
Unsupervised learning by spike timing dependent plasticity in phase change memory (PCM) synapses
S Ambrogio, N Ciocchini, M Laudato, V Milo, A Pirovano, P Fantini, ...
Frontiers in neuroscience 10, 56, 2016
2552016
Multilevel HfO2-based RRAM devices for low-power neuromorphic networks
V Milo, C Zambelli, P Olivo, E Pérez, M K Mahadevaiah, O G Ossorio, ...
APL materials 7 (8), 2019
1952019
Memristive neural network for on-line learning and tracking with brain-inspired spike timing dependent plasticity
G Pedretti, V Milo, S Ambrogio, R Carboni, S Bianchi, A Calderoni, ...
Scientific reports 7 (1), 5288, 2017
1822017
Physical unbiased generation of random numbers with coupled resistive switching devices
S Balatti, S Ambrogio, R Carboni, V Milo, Z Wang, A Calderoni, ...
IEEE Transactions on Electron Devices 63 (5), 2029-2035, 2016
1342016
Memristive and CMOS devices for neuromorphic computing
V Milo, G Malavena, C Monzio Compagnoni, D Ielmini
Materials 13 (1), 166, 2020
1312020
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
892021
Demonstration of hybrid CMOS/RRAM neural networks with spike time/rate-dependent plasticity
V Milo, G Pedretti, R Carboni, A Calderoni, N Ramaswamy, S Ambrogio, ...
2016 IEEE International Electron Devices Meeting (IEDM), 16.8. 1-16.8. 4, 2016
862016
Physics-based modeling approaches of resistive switching devices for memory and in-memory computing applications
D Ielmini, V Milo
Journal of Computational Electronics 16, 1121-1143, 2017
802017
Stochastic learning in neuromorphic hardware via spike timing dependent plasticity with RRAM synapses
G Pedretti, V Milo, S Ambrogio, R Carboni, S Bianchi, A Calderoni, ...
IEEE Journal on Emerging and Selected Topics in Circuits and Systems 8 (1 …, 2017
502017
Analytical Modeling of Organic–Inorganic CH3NH3PbI3 Perovskite Resistive Switching and its Application for Neuromorphic Recognition
Y Ren, V Milo, Z Wang, H Xu, D Ielmini, X Zhao, Y Liu
Advanced Theory and Simulations 1 (4), 1700035, 2018
472018
Novel RRAM-enabled 1T1R synapse capable of low-power STDP via burst-mode communication and real-time unsupervised machine learning
S Ambrogio, S Balatti, V Milo, R Carboni, Z Wang, A Calderoni, ...
2016 IEEE Symposium on VLSI Technology, 1-2, 2016
442016
A 4-transistors/1-resistor hybrid synapse based on resistive switching memory (RRAM) capable of spike-rate-dependent plasticity (SRDP)
V Milo, G Pedretti, R Carboni, A Calderoni, N Ramaswamy, S Ambrogio, ...
IEEE Transactions on Very Large Scale Integration (VLSI) Systems 26 (12 …, 2018
382018
Computing of temporal information in spiking neural networks with ReRAM synapses
W Wang, G Pedretti, V Milo, R Carboni, A Calderoni, N Ramaswamy, ...
Faraday discussions 213, 453-469, 2019
372019
A spiking recurrent neural network with phase-change memory neurons and synapses for the accelerated solution of constraint satisfaction problems
G Pedretti, P Mannocci, S Hashemkhani, V Milo, O Melnic, E Chicca, ...
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits 6 …, 2020
362020
Attractor networks and associative memories with STDP learning in RRAM synapses
V Milo, D Ielmini, E Chicca
2017 IEEE International Electron Devices Meeting (IEDM), 11.2. 1-11.2. 4, 2017
352017
Optimized programming algorithms for multilevel RRAM in hardware neural networks
V Milo, F Anzalone, C Zambelli, E Pérez, MK Mahadevaiah, ÓG Ossorio, ...
2021 IEEE International Reliability Physics Symposium (IRPS), 1-6, 2021
342021
Analytical modeling of current overshoot in oxide-based resistive switching memory (RRAM)
S Ambrogio, V Milo, ZQ Wang, S Balatti, D Ielmini
IEEE Electron Device Letters 37 (10), 1268-1271, 2016
332016
Modeling-based design of brain-inspired spiking neural networks with RRAM learning synapses
G Pedretti, S Bianchi, V Milo, A Calderoni, N Ramaswamy, D Ielmini
2017 IEEE International Electron Devices Meeting (IEDM), 28.1. 1-28.1. 4, 2017
302017
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