S. Ambrogio

发表

Analytical Modeling of Oxide-Based Bipolar Resistive Memories and Complementary Resistive Switches

S. Ambrogio, S. Balatti, D. Gilmer, 2014, IEEE Transactions on Electron Devices.

Spike-timing dependent plasticity in a transistor-selected resistive switching memory

S. Ambrogio, S. Balatti, D. Ielmini, 2013, Nanotechnology.

Normally-off Logic Based on Resistive Switches—Part I: Logic Gates

S. Ambrogio, S. Balatti, D. Ielmini, 2015, IEEE Transactions on Electron Devices.

Recent progress in analog memory-based accelerators for deep learning

P. Narayanan, G. Burr, S. Ambrogio, 2018, Journal of Physics D: Applied Physics.

Understanding switching variability and random telegraph noise in resistive RAM

S. Ambrogio, S. Balatti, D. Ielmini, 2013, 2013 IEEE International Electron Devices Meeting.

Voltage-dependent random telegraph noise (RTN) in HfOx resistive RAM

S. Ambrogio, S. Balatti, D. Ielmini, 2014, 2014 IEEE International Reliability Physics Symposium.

Emerging neuromorphic devices

S. Ambrogio, D. Ielmini, 2019, Nanotechnology.

ReRAM‐Based Neuromorphic Computing

S. Ambrogio, E. Linn, G. Indiveri, 2016 .

Enabling High-Performance DNN Inference Accelerators Using Non-Volatile Analog Memory (Invited)

Pritish Narayanan, Geoffrey W. Burr, Stefano Ambrogio, 2020, 2020 4th IEEE Electron Devices Technology & Manufacturing Conference (EDTM).

Weight Programming in DNN Analog Hardware Accelerators in the Presence of NVM Variability

P. Narayanan, G. Burr, S. Ambrogio, 2019, Advanced Electronic Materials.

Cycling-induced degradation of metal-oxide resistive switching memory (RRAM)

S. Ambrogio, S. Balatti, D. Ielmini, 2015, 2015 IEEE International Electron Devices Meeting (IEDM).

Accelerated Retention Test Method by Controlling Ion Migration Barrier of Resistive Random Access Memory

H. Hwang, S. Ambrogio, D. Ielmini, 2015, IEEE Electron Device Letters.

Modeling resistive switching materials and devices across scales

S. Ambrogio, Y. Nishi, A. Strachan, 2017, Journal of Electroceramics.

Statistical Fluctuations in HfOx Resistive-Switching Memory: Part II—Random Telegraph Noise

S. Ambrogio, S. Balatti, D. Ielmini, 2014, IEEE Transactions on Electron Devices.

the mid-1980 s with the collaboration that sprung up between prominent scien

S. Ambrogio, G. Indiveri, 2015 .

Analytical modelling and leakage optimization in complementary resistive switch (CRS) crossbar arrays

Stefano Ambrogio, Simone Balatti, Daniele Ielmini, 2014, 2014 44th European Solid State Device Research Conference (ESSDERC).

ACT-TILT Project (Work Package 1.2.1): Hinge Moments Estimation

Eugenio Denti, G. Di Rito, S. Ambrogio, 2002 .

Optimised weight programming for analogue memory-based deep neural networks

M. Rasch, P. Narayanan, G. Burr, 2022, Nature Communications.

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S. Ambrogio, S. Balatti, D. Ielmini, 2014 .

Fully on-chip MAC at 14nm enabled by accurate row-wise programming of PCM-based weights and parallel vector-transport in duration-format

P. Narayanan, I. Ahsan, G. Burr, 2021, 2021 Symposium on VLSI Technology.

(Invited) Resistive Switching in Metal Oxides: From Physical Modeling to Device Scaling

S. Ambrogio, S. Balatti, D. Ielmini, 2013 .

Impact of the Mechanical Stress on Switching Characteristics of Electrochemical Resistive Memory

Stefano Ambrogio, Simone Balatti, Daniele Ielmini, 2014, Advanced materials.

Neuromorphic Learning and Recognition With One-Transistor-One-Resistor Synapses and Bistable Metal Oxide RRAM

Alessandro Calderoni, Stefano Ambrogio, Simone Balatti, 2016, IEEE Transactions on Electron Devices.

Pulsed cycling operation and endurance failure of metal-oxide resistive (RRAM)

D. Ielmini, S. Ambrogio, N. Ramaswamy, 2014, 2014 IEEE International Electron Devices Meeting.

Memristive neural network for on-line learning and tracking with brain-inspired spike timing dependent plasticity

A S Spinelli, G Pedretti, V Milo, 2017, Scientific Reports.

Equivalent-accuracy accelerated neural-network training using analogue memory

Nathan C. P. Farinha, P. Narayanan, G. Burr, 2018, Nature.

Understanding cycling endurance in perpendicular spin-transfer torque (p-STT) magnetic memory

D. Ielmini, R. Carboni, M. Siddik, 2016, 2016 IEEE International Electron Devices Meeting (IEDM).

Physical Unbiased Generation of Random Numbers With Coupled Resistive Switching Devices

Alessandro Calderoni, Stefano Ambrogio, Simone Balatti, 2016, IEEE Transactions on Electron Devices.

Voltage-Controlled Cycling Endurance of HfOx-Based Resistive-Switching Memory

Alessandro Calderoni, Stefano Ambrogio, Simone Balatti, 2015, IEEE Transactions on Electron Devices.

True Random Number Generation by Variability of Resistive Switching in Oxide-Based Devices

Stefano Ambrogio, Simone Balatti, Daniele Ielmini, 2015, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

Unsupervised Learning by Spike Timing Dependent Plasticity in Phase Change Memory (PCM) Synapses

Paolo Fantini, Daniele Ielmini, Valerio Milo, 2016, Front. Neurosci..

Nagarajan Raghavan, Jordi Suñé, H.-S. Philip Wong, 2018, Advanced Electronic Materials.

Memristive neural network for on-line learning and tracking with brain-inspired spike timing dependent plasticity

S. Ambrogio, D. Ielmini, A. Spinelli, 2017, Scientific Reports.

A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning in neuromorphic systems

Simone Balatti, Daniele Ielmini, Stefano Ambrogio, 2015, Front. Neurosci..

Equivalent-accuracy accelerated neural-network training using analogue memory

Pritish Narayanan, Stefano Ambrogio, Irem Boybat, 2018, Nature.

Analog-to-Digital Conversion With Reconfigurable Function Mapping for Neural Networks Activation Function Acceleration

Pritish Narayanan, Koji Ishibashi, Stefano Ambrogio, 2019, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

Energy-efficient continual learning in hybrid supervised-unsupervised neural networks with PCM synapses

D. Ielmini, I. Muñoz-Martin, S. Bianchi, 2019, 2019 Symposium on VLSI Technology.

Unsupervised Learning to Overcome Catastrophic Forgetting in Neural Networks

Daniele Ielmini, Giacomo Pedretti, Stefano Ambrogio, 2019, IEEE Journal on Exploratory Solid-State Computational Devices and Circuits.

Ultrafast valley relaxation dynamics in monolayer MoS2 probed by nonequilibrium optical techniques

Eva A. A. Pogna, S. D. Conte, S. Ambrogio, 2015 .

Toward Software-Equivalent Accuracy on Transformer-Based Deep Neural Networks With Analog Memory Devices

Pritish Narayanan, Stefano Ambrogio, Hsinyu Tsai, 2021, Frontiers in Computational Neuroscience.

Reducing the Impact of Phase-Change Memory Conductance Drift on the Inference of large-scale Hardware Neural Networks

S. Ambrogio, A. Kumar, A. Chen, 2019, 2019 IEEE International Electron Devices Meeting (IEDM).

AI hardware acceleration with analog memory: Microarchitectures for low energy at high speed

Pritish Narayanan, Scott C. Lewis, Geoffrey W. Burr, 2019, IBM J. Res. Dev..

Inference of Long-Short Term Memory networks at software-equivalent accuracy using 2.5M analog Phase Change Memory devices

R. M. Shelby, P. Narayanan, H. Tsai, 2019, 2019 Symposium on VLSI Technology.

Intervalley scattering in monolayer MoS2 probed by non-equilibrium optical techniques

S. Ambrogio, A. C. Ferrari, G. Cerullo, 2015, SPIE NanoScience + Engineering.

Postcycling Degradation in Metal-Oxide Bipolar Resistive Switching Memory

Alessandro Calderoni, Stefano Ambrogio, Simone Balatti, 2016, IEEE Transactions on Electron Devices.

Statistical Fluctuations in HfOx Resistive-Switching Memory: Part I - Set/Reset Variability

Alessandro Calderoni, Stefano Ambrogio, Simone Balatti, 2014, IEEE Transactions on Electron Devices.

Set Variability and Failure Induced by Complementary Switching in Bipolar RRAM

D. Ielmini, S. Ambrogio, S. Balatti, 2013, IEEE Electron Device Letters.

Understanding pulsed-cycling variability and endurance in HfOx RRAM

Alessandro Calderoni, Stefano Ambrogio, Simone Balatti, 2015, 2015 IEEE International Reliability Physics Symposium.

Noise-Induced Resistance Broadening in Resistive Switching Memory—Part I: Intrinsic Cell Behavior

Stefano Ambrogio, Simone Balatti, Daniele Ielmini, 2015, IEEE Transactions on Electron Devices.

Impact of low-frequency noise on read distributions of resistive switching memory (RRAM)

D. Ielmini, S. Ambrogio, S. Balatti, 2014, 2014 IEEE International Electron Devices Meeting.

Noise-Resilient DNN: Tolerating Noise in PCM-Based AI Accelerators via Noise-Aware Training

Moinuddin K. Qureshi, P. Narayanan, G. Burr, 2021, IEEE Transactions on Electron Devices.

Modeling of Breakdown-Limited Endurance in Spin-Transfer Torque Magnetic Memory Under Pulsed Cycling Regime

Stefano Ambrogio, Daniele Ielmini, Roberto Carboni, 2018, IEEE Transactions on Electron Devices.

An analog-AI chip for energy-efficient speech recognition and transcription

P. Narayanan, I. Ahsan, G. Burr, 2023, Nature.

Analog-memory-based 14nm Hardware Accelerator for Dense Deep Neural Networks including Transformers

M. Rasch, P. Narayanan, G. Burr, 2022, International Symposium on Circuits and Systems.

Mushroom-Type phase change memory with projection liner: An array-level demonstration of conductance drift and noise mitigation

S. Ambrogio, A. Sebastian, T. Yamashita, 2021, 2021 IEEE International Reliability Physics Symposium (IRPS).

A Compact Model for Stochastic Spike-Timing-Dependent Plasticity (STDP) Based on Resistive Switching Memory (RRAM) Synapses

Stefano Ambrogio, Daniele Ielmini, Giacomo Pedretti, 2020, IEEE Transactions on Electron Devices.

Confined PCM-based Analog Synaptic Devices offering Low Resistance-drift and 1000 Programmable States for Deep Learning

S. Ambrogio, K. Suu, J. Bruley, 2019, 2019 Symposium on VLSI Technology.

Energy-efficient continual learning in hybrid supervised-unsupervised neural networks with PCM synapses

Daniele Ielmini, Giacomo Pedretti, Stefano Ambrogio, 2019, 2019 Symposium on VLSI Technology.

Valley and spin dynamics in monolayer MoS$_{2}$

Eva A. A. Pogna, S. D. Conte, S. Ambrogio, 2015, 1502.06817.

Analog acceleration of deep learning using phase-change memory

Pritish Narayanan, Geoffrey W. Burr, Stefano Ambrogio, 2020 .

Neuromorphic computing with resistive switching memory devices

Daniele Ielmini, Stefano Ambrogio, S. Ambrogio, 2019, Advances in Non-Volatile Memory and Storage Technology.

Spike-timing dependent plasticity in a transistor-selected resistive switching memory

S. Ambrogio, S. Balatti, F. Nardi, 2013, Nanotechnology.

Noise-Induced Resistance Broadening in Resistive Switching Memory—Part II: Array Statistics

Stefano Ambrogio, Simone Balatti, Daniele Ielmini, 2015, IEEE Transactions on Electron Devices.