| In materia reservoir computing with a fully memristive architecture based on self-organizing nanowire networks G Milano, G Pedretti, K Montano, S Ricci, S Hashemkhani, L Boarino, ... Nature materials 21 (2), 195-202, 2022 | 341 | 2022 |
| 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 | 282 | 2018 |
| Solving matrix equations in one step with cross-point resistive arrays Z Sun, G Pedretti, E Ambrosi, A Bricalli, W Wang, D Ielmini Proceedings of the National Academy of Sciences 116 (10), 4123-4128, 2019 | 250 | 2019 |
| 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 | 182 | 2017 |
| Analog content-addressable memories with memristors C Li, CE Graves, X Sheng, D Miller, M Foltin, G Pedretti, JP Strachan Nature communications 11 (1), 1638, 2020 | 178 | 2020 |
| Device and circuit architectures for in‐memory computing D Ielmini, G Pedretti Advanced Intelligent Systems 2 (7), 2000040, 2020 | 158 | 2020 |
| Brain‐inspired structural plasticity through reweighting and rewiring in multi‐terminal self‐organizing memristive nanowire networks G Milano, G Pedretti, M Fretto, L Boarino, F Benfenati, D Ielmini, I Valov, ... Advanced Intelligent Systems 2 (8), 2000096, 2020 | 121 | 2020 |
| One-step regression and classification with cross-point resistive memory arrays Z Sun, G Pedretti, A Bricalli, D Ielmini Science advances 6 (5), eaay2378, 2020 | 114 | 2020 |
| Tree-based machine learning performed in-memory with memristive analog CAM G Pedretti, CE Graves, C Li, S Serebryakov, X Sheng, M Foltin, R Mao, ... Nature communications 12 (5806), 1-10, 2021 | 90 | 2021 |
| 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 | 89 | 2016 |
| In-memory computing with resistive memory circuits: Status and outlook G Pedretti, D Ielmini Electronics 10 (9), 1063, 2021 | 65 | 2021 |
| Neuromorphic motion detection and orientation selectivity by volatile resistive switching memories W Wang, E Covi, A Milozzi, M Farronato, S Ricci, C Sbandati, G Pedretti, ... Advanced Intelligent Systems 3 (4), 2000224, 2021 | 61 | 2021 |
| In-memory PageRank accelerator with a cross-point array of resistive memories Z Sun, E Ambrosi, G Pedretti, A Bricalli, D Ielmini IEEE Transactions on Electron Devices 67 (4), 1466-1470, 2020 | 50 | 2020 |
| 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 | 50 | 2017 |
| Time complexity of in-memory solution of linear systems Z Sun, G Pedretti, P Mannocci, E Ambrosi, A Bricalli, D Ielmini IEEE Transactions on Electron Devices 67 (7), 2945-2951, 2020 | 44 | 2020 |
| Unsupervised learning to overcome catastrophic forgetting in neural networks I Munoz-Martin, S Bianchi, G Pedretti, O Melnic, S Ambrogio, D Ielmini IEEE Journal on Exploratory Solid-State Computational Devices and Circuits 5 …, 2019 | 38 | 2019 |
| 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 | 37 | 2019 |
| 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 | 36 | 2020 |
| 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 | 36 | 2018 |
| 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 | 29 | 2017 |
Daniele IelminiProfessor of ElectronicsGeverifieerd e-mailadres voor elet.polimi.it
