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Irem Boybat

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

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Frontiers in Neuroscience|August 26, 2022
Editorial: Hardware for artificial intelligenceIrem Boybat, Melika Payvand, Oliver Rhodes, et al.
Scientific Reports|May 17, 2020
Experimental Demonstration of Supervised Learning in Spiking Neural Networks with Phase-Change Memory SynapsesS R Nandakumar, Irem Boybat, Manuel Le Gallo, et al.
Nature Communications|May 20, 2020
Accurate deep neural network inference using computational phase-change memoryVinay Joshi, Manuel Le Gallo, Simon Haefeli, et al.
Nature Communications|June 30, 2018
Neuromorphic computing with multi-memristive synapsesIrem Boybat, Manuel Le Gallo, S R Nandakumar, et al.
Nature Communications|March 28, 2026
Supernetwork-based efficient mapping of deep learning applications to mixed-precision hardware using model adaptationHadjer Benmeziane, Corey Lammie, Irem Boybat, et al.
Nature Computational Science|January 8, 2025
Efficient scaling of large language models with mixture of experts and 3D analog in-memory computingJulian Büchel, Athanasios Vasilopoulos, William Andrew Simon, et al.
Frontiers in Neuroscience|June 2, 2020
Mixed-Precision Deep Learning Based on Computational MemoryS R Nandakumar, Manuel Le Gallo, Christophe Piveteau, et al.
Nature|June 8, 2018
Equivalent-accuracy accelerated neural-network training using analogue memoryStefano Ambrogio, Pritish Narayanan, Hsinyu Tsai, et al.
ACS Nano|June 29, 2023
Recent Advances and Future Prospects for Memristive Materials, Devices, and SystemsMin-Kyu Song, Ji-Hoon Kang, Xinyuan Zhang, et al.
Pageof 1

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

Sort By:
Pageof 1
Frontiers in Neuroscience|August 26, 2022
Editorial: Hardware for artificial intelligenceIrem Boybat, Melika Payvand, Oliver Rhodes, et al.
Scientific Reports|May 17, 2020
Experimental Demonstration of Supervised Learning in Spiking Neural Networks with Phase-Change Memory SynapsesS R Nandakumar, Irem Boybat, Manuel Le Gallo, et al.
Nature Communications|May 20, 2020
Accurate deep neural network inference using computational phase-change memoryVinay Joshi, Manuel Le Gallo, Simon Haefeli, et al.
Nature Communications|June 30, 2018
Neuromorphic computing with multi-memristive synapsesIrem Boybat, Manuel Le Gallo, S R Nandakumar, et al.
Nature Communications|March 28, 2026
Supernetwork-based efficient mapping of deep learning applications to mixed-precision hardware using model adaptationHadjer Benmeziane, Corey Lammie, Irem Boybat, et al.
Nature Computational Science|January 8, 2025
Efficient scaling of large language models with mixture of experts and 3D analog in-memory computingJulian Büchel, Athanasios Vasilopoulos, William Andrew Simon, et al.
Frontiers in Neuroscience|June 2, 2020
Mixed-Precision Deep Learning Based on Computational MemoryS R Nandakumar, Manuel Le Gallo, Christophe Piveteau, et al.
Nature|June 8, 2018
Equivalent-accuracy accelerated neural-network training using analogue memoryStefano Ambrogio, Pritish Narayanan, Hsinyu Tsai, et al.
ACS Nano|June 29, 2023
Recent Advances and Future Prospects for Memristive Materials, Devices, and SystemsMin-Kyu Song, Ji-Hoon Kang, Xinyuan Zhang, et al.
Pageof 1