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Wilfried Haensch

Showing results (1-10 of 24) with videos related to

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Frontiers in Neuroscience|March 17, 2020
Algorithm for Training Neural Networks on Resistive Device ArraysTayfun Gokmen, Wilfried Haensch
Nature|July 28, 2012
Device physics: Put the pedal to the metalJochen Mannhart, Wilfried Haensch
Frontiers in Neuroscience|October 26, 2017
Training Deep Convolutional Neural Networks with Resistive Cross-Point DevicesTayfun Gokmen, Murat Onen, Wilfried Haensch
Science (New York, N.Y.)|July 9, 2016
ENGINEERING. Solar-powering the Internet of ThingsRichard Haight, Wilfried Haensch, Daniel Friedman
Frontiers in Neuroscience|November 9, 2018
Training LSTM Networks With Resistive Cross-Point DevicesTayfun Gokmen, Malte J Rasch, Wilfried Haensch
Nano Letters|December 22, 2010
Large-scale graphene transistors with enhanced performance and reliability based on interface engineering by phenylsilane self-assembled monolayersZihong Liu, Ageeth A Bol, Wilfried Haensch
ACS Nano|July 8, 2014
Defining and overcoming the contact resistance challenge in scaled carbon nanotube transistorsAaron D Franklin, Damon B Farmer, Wilfried Haensch
Frontiers in Artificial Intelligence|October 21, 2024
LRMP: Layer Replication with Mixed Precision for spatial in-memory DNN acceleratorsAbinand Nallathambi, Christin David Bose, Wilfried Haensch, 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.
ACS Nano|June 8, 2012
Evaluation of field-effect mobility and contact resistance of transistors that use solution-processed single-walled carbon nanotubesQing Cao, Shu-Jen Han, George S Tulevski, et al.
Pageof 3

Showing results (1-10 of 24) with videos related to

Sort By:
Pageof 3
Frontiers in Neuroscience|March 17, 2020
Algorithm for Training Neural Networks on Resistive Device ArraysTayfun Gokmen, Wilfried Haensch
Nature|July 28, 2012
Device physics: Put the pedal to the metalJochen Mannhart, Wilfried Haensch
Frontiers in Neuroscience|October 26, 2017
Training Deep Convolutional Neural Networks with Resistive Cross-Point DevicesTayfun Gokmen, Murat Onen, Wilfried Haensch
Science (New York, N.Y.)|July 9, 2016
ENGINEERING. Solar-powering the Internet of ThingsRichard Haight, Wilfried Haensch, Daniel Friedman
Frontiers in Neuroscience|November 9, 2018
Training LSTM Networks With Resistive Cross-Point DevicesTayfun Gokmen, Malte J Rasch, Wilfried Haensch
Nano Letters|December 22, 2010
Large-scale graphene transistors with enhanced performance and reliability based on interface engineering by phenylsilane self-assembled monolayersZihong Liu, Ageeth A Bol, Wilfried Haensch
ACS Nano|July 8, 2014
Defining and overcoming the contact resistance challenge in scaled carbon nanotube transistorsAaron D Franklin, Damon B Farmer, Wilfried Haensch
Frontiers in Artificial Intelligence|October 21, 2024
LRMP: Layer Replication with Mixed Precision for spatial in-memory DNN acceleratorsAbinand Nallathambi, Christin David Bose, Wilfried Haensch, 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.
ACS Nano|June 8, 2012
Evaluation of field-effect mobility and contact resistance of transistors that use solution-processed single-walled carbon nanotubesQing Cao, Shu-Jen Han, George S Tulevski, et al.
Pageof 3