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Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
|
January 18, 2017
Hebbian plasticity requires compensatory processes on multiple timescales
Friedemann Zenke, Wulfram Gerstner
Frontiers in Neuroinformatics
|
October 14, 2014
Limits to high-speed simulations of spiking neural networks using general-purpose computers
Friedemann Zenke, Wulfram Gerstner
Neural Computation
|
April 14, 2018
SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks
Friedemann Zenke, Surya Ganguli
Neural Computation
|
March 20, 2025
Elucidating the Theoretical Underpinnings of Surrogate Gradient Learning in Spiking Neural Networks
Julia Gygax, Friedemann Zenke
Elife
|
December 13, 2021
Nonlinear transient amplification in recurrent neural networks with short-term plasticity
Yue Kris Wu, Friedemann Zenke
Nature Neuroscience
|
October 12, 2023
The combination of Hebbian and predictive plasticity learns invariant object representations in deep sensory networks
Manu Srinath Halvagal, Friedemann Zenke
Neural Computation
|
January 29, 2021
The Remarkable Robustness of Surrogate Gradient Learning for Instilling Complex Function in Spiking Neural Networks
Friedemann Zenke, Tim P Vogels
Proceedings of Machine Learning Research
|
January 8, 2020
Continual Learning Through Synaptic Intelligence
Friedemann Zenke, Ben Poole, Surya Ganguli
Plos Computational Biology
|
November 19, 2013
Synaptic plasticity in neural networks needs homeostasis with a fast rate detector
Friedemann Zenke, Guillaume Hennequin, Wulfram Gerstner
Frontiers in Computational Neuroscience
|
December 10, 2015
Editorial: Emergent Neural Computation from the Interaction of Different Forms of Plasticity
Matthieu Gilson, Cristina Savin, Friedemann Zenke
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of 3
Search research articles
Search
Showing results (1-10 of 25) with videos related to
Sort By:
Page
of 3
Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
|
January 18, 2017
Hebbian plasticity requires compensatory processes on multiple timescales
Friedemann Zenke, Wulfram Gerstner
Frontiers in Neuroinformatics
|
October 14, 2014
Limits to high-speed simulations of spiking neural networks using general-purpose computers
Friedemann Zenke, Wulfram Gerstner
Neural Computation
|
April 14, 2018
SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks
Friedemann Zenke, Surya Ganguli
Neural Computation
|
March 20, 2025
Elucidating the Theoretical Underpinnings of Surrogate Gradient Learning in Spiking Neural Networks
Julia Gygax, Friedemann Zenke
Elife
|
December 13, 2021
Nonlinear transient amplification in recurrent neural networks with short-term plasticity
Yue Kris Wu, Friedemann Zenke
Nature Neuroscience
|
October 12, 2023
The combination of Hebbian and predictive plasticity learns invariant object representations in deep sensory networks
Manu Srinath Halvagal, Friedemann Zenke
Neural Computation
|
January 29, 2021
The Remarkable Robustness of Surrogate Gradient Learning for Instilling Complex Function in Spiking Neural Networks
Friedemann Zenke, Tim P Vogels
Proceedings of Machine Learning Research
|
January 8, 2020
Continual Learning Through Synaptic Intelligence
Friedemann Zenke, Ben Poole, Surya Ganguli
Plos Computational Biology
|
November 19, 2013
Synaptic plasticity in neural networks needs homeostasis with a fast rate detector
Friedemann Zenke, Guillaume Hennequin, Wulfram Gerstner
Frontiers in Computational Neuroscience
|
December 10, 2015
Editorial: Emergent Neural Computation from the Interaction of Different Forms of Plasticity
Matthieu Gilson, Cristina Savin, Friedemann Zenke
Page
of 3