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Tayfun Gokmen

Showing results (1-10 of 12) with videos related to

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Frontiers in Artificial Intelligence|September 27, 2021
Enabling Training of Neural Networks on Noisy HardwareTayfun Gokmen
Frontiers in Neuroscience|March 17, 2020
Algorithm for Training Neural Networks on Resistive Device ArraysTayfun Gokmen, Wilfried Haensch
Frontiers in Neuroscience|August 6, 2016
Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices: Design ConsiderationsTayfun Gokmen, Yurii Vlasov
Frontiers in Neuroscience|October 26, 2017
Training Deep Convolutional Neural Networks with Resistive Cross-Point DevicesTayfun Gokmen, Murat Onen, Wilfried Haensch
Frontiers in Neuroscience|November 9, 2018
Training LSTM Networks With Resistive Cross-Point DevicesTayfun Gokmen, Malte J Rasch, Wilfried Haensch
Nature Communications|August 20, 2024
Fast and robust analog in-memory deep neural network trainingMalte J Rasch, Fabio Carta, Omobayode Fagbohungbe, et al.
Frontiers in Neuroscience|August 17, 2019
RAPA-ConvNets: Modified Convolutional Networks for Accelerated Training on Architectures With Analog ArraysMalte J Rasch, Tayfun Gokmen, Mattia Rigotti, et al.
Frontiers in Neuroscience|January 24, 2022
Impact of Asymmetric Weight Update on Neural Network Training With Tiki-Taka AlgorithmChaeun Lee, Kyungmi Noh, Wonjae Ji, et al.
Nanotechnology|September 26, 2019
Design and characterization of superconducting nanowire-based processors for acceleration of deep neural network trainingMurat Onen, Brenden A Butters, Emily Toomey, et al.
Frontiers in Artificial Intelligence|May 26, 2022
Neural Network Training With Asymmetric Crosspoint ElementsMurat Onen, Tayfun Gokmen, Teodor K Todorov, et al.
Pageof 2

Showing results (1-10 of 12) with videos related to

Sort By:
Pageof 2
Frontiers in Artificial Intelligence|September 27, 2021
Enabling Training of Neural Networks on Noisy HardwareTayfun Gokmen
Frontiers in Neuroscience|March 17, 2020
Algorithm for Training Neural Networks on Resistive Device ArraysTayfun Gokmen, Wilfried Haensch
Frontiers in Neuroscience|August 6, 2016
Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices: Design ConsiderationsTayfun Gokmen, Yurii Vlasov
Frontiers in Neuroscience|October 26, 2017
Training Deep Convolutional Neural Networks with Resistive Cross-Point DevicesTayfun Gokmen, Murat Onen, Wilfried Haensch
Frontiers in Neuroscience|November 9, 2018
Training LSTM Networks With Resistive Cross-Point DevicesTayfun Gokmen, Malte J Rasch, Wilfried Haensch
Nature Communications|August 20, 2024
Fast and robust analog in-memory deep neural network trainingMalte J Rasch, Fabio Carta, Omobayode Fagbohungbe, et al.
Frontiers in Neuroscience|August 17, 2019
RAPA-ConvNets: Modified Convolutional Networks for Accelerated Training on Architectures With Analog ArraysMalte J Rasch, Tayfun Gokmen, Mattia Rigotti, et al.
Frontiers in Neuroscience|January 24, 2022
Impact of Asymmetric Weight Update on Neural Network Training With Tiki-Taka AlgorithmChaeun Lee, Kyungmi Noh, Wonjae Ji, et al.
Nanotechnology|September 26, 2019
Design and characterization of superconducting nanowire-based processors for acceleration of deep neural network trainingMurat Onen, Brenden A Butters, Emily Toomey, et al.
Frontiers in Artificial Intelligence|May 26, 2022
Neural Network Training With Asymmetric Crosspoint ElementsMurat Onen, Tayfun Gokmen, Teodor K Todorov, et al.
Pageof 2