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Stefano Ambrogio

Showing results (1-10 of 9) with videos related to

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Nanotechnology|November 8, 2019
Emerging neuromorphic devicesDaniele Ielmini, Stefano Ambrogio
Frontiers in Neuroscience|February 3, 2015
A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning in neuromorphic systemsZhongqiang Wang, Stefano Ambrogio, Simone Balatti, et al.
Advanced Materials (Deerfield Beach, Fla.)|March 27, 2014
Impact of the mechanical stress on switching characteristics of electrochemical resistive memoryStefano Ambrogio, Simone Balatti, Seol Choi, et al.
Frontiers in Neuroscience|March 26, 2016
Unsupervised Learning by Spike Timing Dependent Plasticity in Phase Change Memory (PCM) SynapsesStefano Ambrogio, Nicola Ciocchini, Mario Laudato, et al.
Faraday Discussions|October 26, 2018
Training fully connected networks with resistive memories: impact of device failuresLouis P Romero, Stefano Ambrogio, Massimo Giordano, et al.
Frontiers in Computational Neuroscience|July 22, 2021
Toward Software-Equivalent Accuracy on Transformer-Based Deep Neural Networks With Analog Memory DevicesKatie Spoon, Hsinyu Tsai, An Chen, et al.
Nature|June 8, 2018
Equivalent-accuracy accelerated neural-network training using analogue memoryStefano Ambrogio, Pritish Narayanan, Hsinyu Tsai, et al.
Nature Communications|June 30, 2022
Optimised weight programming for analogue memory-based deep neural networksCharles Mackin, Malte J Rasch, An Chen, et al.
Nature Communications|September 30, 2025
Demonstration of transformer-based ALBERT model on a 14nm analog AI inference chipAn Chen, Stefano Ambrogio, Pritish Narayanan, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Nanotechnology|November 8, 2019
Emerging neuromorphic devicesDaniele Ielmini, Stefano Ambrogio
Frontiers in Neuroscience|February 3, 2015
A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning in neuromorphic systemsZhongqiang Wang, Stefano Ambrogio, Simone Balatti, et al.
Advanced Materials (Deerfield Beach, Fla.)|March 27, 2014
Impact of the mechanical stress on switching characteristics of electrochemical resistive memoryStefano Ambrogio, Simone Balatti, Seol Choi, et al.
Frontiers in Neuroscience|March 26, 2016
Unsupervised Learning by Spike Timing Dependent Plasticity in Phase Change Memory (PCM) SynapsesStefano Ambrogio, Nicola Ciocchini, Mario Laudato, et al.
Faraday Discussions|October 26, 2018
Training fully connected networks with resistive memories: impact of device failuresLouis P Romero, Stefano Ambrogio, Massimo Giordano, et al.
Frontiers in Computational Neuroscience|July 22, 2021
Toward Software-Equivalent Accuracy on Transformer-Based Deep Neural Networks With Analog Memory DevicesKatie Spoon, Hsinyu Tsai, An Chen, et al.
Nature|June 8, 2018
Equivalent-accuracy accelerated neural-network training using analogue memoryStefano Ambrogio, Pritish Narayanan, Hsinyu Tsai, et al.
Nature Communications|June 30, 2022
Optimised weight programming for analogue memory-based deep neural networksCharles Mackin, Malte J Rasch, An Chen, et al.
Nature Communications|September 30, 2025
Demonstration of transformer-based ALBERT model on a 14nm analog AI inference chipAn Chen, Stefano Ambrogio, Pritish Narayanan, et al.
Pageof 1