Friedemann Zenke

According to our database, Friedemann Zenke authored at least 34 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Decoding finger velocity from cortical spike trains with recurrent spiking neural networks.

Tengjun Liu, Julia Gygax, Julian Rossbroich, Yansong Chua, Shaomin Zhang, Friedemann Zenke

CoRR, 2024

Resource-Efficient Speech Quality Prediction through Quantization Aware Training and Binary Activation Maps.

Mattias Nilsson, Riccardo Miccini, Clément Laroche, Tobias Piechowiak, Friedemann Zenke

CoRR, 2024

Theories of synaptic memory consolidation and intelligent plasticity for continual learning.

Friedemann Zenke, Axel Laborieux

CoRR, 2024

Elucidating the theoretical underpinnings of surrogate gradient learning in spiking neural networks.

Julia Gygax, Friedemann Zenke

CoRR, 2024

Improving equilibrium propagation without weight symmetry through Jacobian homeostasis.

Axel Laborieux, Friedemann Zenke

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Invited: Achieving PetaOps/W Edge-AI Processing.

Manil Dev Gomony, Bas Ahn, Rick Luiken, Yashvardhan Biyani, Anteneh Gebregiorgis, Axel Laborieux, Friedemann Zenke, Said Hamdioui, Henk Corporaal

Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

2023

Editorial: Focus issue on machine learning for neuromorphic engineering.

Melika Payvand, Emre Neftci, Friedemann Zenke

Neuromorph. Comput. Eng., September, 2023

Dis-inhibitory neuronal circuits can control the sign of synaptic plasticity.

Julian Rossbroich, Friedemann Zenke

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Implicit variance regularization in non-contrastive SSL.

Manu Srinath Halvagal, Axel Laborieux, Friedemann Zenke

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PetaOps/W edge-AI $\mu$ Processors: Myth or reality?

Manil Dev Gomony, Floran de Putter, Anteneh Gebregiorgis, Gianna Paulin, Linyan Mei, Vikram Jain, Said Hamdioui, Victor Sanchez, Tobias Grosser, Marc Geilen, Marian Verhelst, Friedemann Zenke, Frank K. Gürkaynak, Barry de Bruin, Sander Stuijk, Simon Davidson, Sayandip De, Mounir Ghogho, Alexandra Jimborean, Sherif Eissa, Luca Benini, Dimitrios Soudris, Rajendra Bishnoi, Sam Ainsworth, Federico Corradi, Ouassim Karrakchou, Tim Güneysu, Henk Corporaal

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023

2022

Fluctuation-driven initialization for spiking neural network training.

Julian Rossbroich, Julia Gygax, Friedemann Zenke

Neuromorph. Comput. Eng., December, 2022

Heidelberg Spiking Datasets.

Benjamin Cramer, Yannik Stradmann, Johannes Schemmel, Friedemann Zenke

Dataset, May, 2022

The Heidelberg Spiking Data Sets for the Systematic Evaluation of Spiking Neural Networks.

Benjamin Cramer, Yannik Stradmann, Johannes Schemmel, Friedemann Zenke

IEEE Trans. Neural Networks Learn. Syst., 2022

Surrogate gradients for analog neuromorphic computing.

Benjamin Cramer, Sebastian Billaudelle, Simeon Kanya, Aron Leibfried, Andreas Grübl, Vitali Karasenko, Christian Pehle, Korbinian Schreiber, Yannik Stradmann, Johannes Weis, Johannes Schemmel, Friedemann Zenke

Proc. Natl. Acad. Sci. USA, 2022

Predictor networks and stop-grads provide implicit variance regularization in BYOL/SimSiam.

Manu Srinath Halvagal, Axel Laborieux, Friedemann Zenke

CoRR, 2022

Braille Letter Reading: A Benchmark for Spatio-Temporal Pattern Recognition on Neuromorphic Hardware.

Simon F. Müller-Cleve, Vittorio Fra, Lyes Khacef, Alejandro Pequeño-Zurro, Daniel Klepatsch, Evelina Forno, Diego Gigena Ivanovich, Shavika Rastogi, Gianvito Urgese, Friedemann Zenke, Chiara Bartolozzi

CoRR, 2022

Holomorphic Equilibrium Propagation Computes Exact Gradients Through Finite Size Oscillations.

Axel Laborieux, Friedemann Zenke

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Brain-Inspired Learning on Neuromorphic Substrates.

Friedemann Zenke, Emre O. Neftci

Proc. IEEE, 2021

The Remarkable Robustness of Surrogate Gradient Learning for Instilling Complex Function in Spiking Neural Networks.

Friedemann Zenke, Tim P. Vogels

Neural Comput., 2021

2020

Training spiking multi-layer networks with surrogate gradients on an analog neuromorphic substrate.

Benjamin Cramer, Sebastian Billaudelle, Simeon Kanya, Aron Leibfried, Andreas Grübl, Vitali Karasenko, Christian Pehle, Korbinian Schreiber, Yannik Stradmann, Johannes Weis, Johannes Schemmel, Friedemann Zenke

CoRR, 2020

A meta-learning approach to (re)discover plasticity rules that carve a desired function into a neural network.

Basile Confavreux, Friedemann Zenke, Everton J. Agnes, Timothy P. Lillicrap, Tim P. Vogels

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Finding trainable sparse networks through Neural Tangent Transfer.

Tianlin Liu, Friedemann Zenke

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Surrogate Gradient Learning in Spiking Neural Networks: Bringing the Power of Gradient-based optimization to spiking neural networks.

Emre O. Neftci, Hesham Mostafa, Friedemann Zenke

IEEE Signal Process. Mag., 2019

The Heidelberg spiking datasets for the systematic evaluation of spiking neural networks.

Benjamin Cramer, Yannik Stradmann, Johannes Schemmel, Friedemann Zenke

CoRR, 2019

Surrogate Gradient Learning in Spiking Neural Networks.

Emre O. Neftci, Hesham Mostafa, Friedemann Zenke

CoRR, 2019

2018

SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks.

Friedemann Zenke, Surya Ganguli

Neural Comput., 2018

2017

Improved multitask learning through synaptic intelligence.

Friedemann Zenke, Ben Poole, Surya Ganguli

CoRR, 2017

SuperSpike: Supervised learning in multi-layer spiking neural networks.

Friedemann Zenke, Surya Ganguli

CoRR, 2017

Continual Learning Through Synaptic Intelligence.

Friedemann Zenke, Ben Poole, Surya Ganguli

Proceedings of the 34th International Conference on Machine Learning, 2017

Intelligent synapses for multi-task and transfer learning.

Ben Poole, Friedemann Zenke, Surya Ganguli

Proceedings of the 5th International Conference on Learning Representations, 2017

2015

Editorial: Emergent Neural Computation from the Interaction of Different Forms of Plasticity.

Matthieu Gilson, Cristina Savin, Friedemann Zenke

Frontiers Comput. Neurosci., 2015

2014

Memory formation and recall in recurrent spiking neural networks.

Friedemann Zenke

PhD thesis, 2014

Limits to high-speed simulations of spiking neural networks using general-purpose computers.

Friedemann Zenke, Wulfram Gerstner

Frontiers Neuroinformatics, 2014

2013

Synaptic Plasticity in Neural Networks Needs Homeostasis with a Fast Rate Detector.

Friedemann Zenke, Guillaume Hennequin, Wulfram Gerstner

PLoS Comput. Biol., 2013