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Henning Sprekeler
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2020 – today
- 2024
- [j20]Halil Yigit Öksüz
, Fabio Molinari
, Henning Sprekeler, Jörg Raisch
:
Boosting Fairness and Robustness in Over-the-Air Federated Learning. IEEE Control. Syst. Lett. 8: 682-687 (2024) - [i7]Halil Yigit Öksüz, Fabio Molinari, Henning Sprekeler, Jörg Raisch:
Boosting Fairness and Robustness in Over-the-Air Federated Learning. CoRR abs/2403.04431 (2024) - [i6]Jarek Liesen, Chris Lu, Andrei Lupu, Jakob N. Foerster, Henning Sprekeler, Robert T. Lange:
Discovering Minimal Reinforcement Learning Environments. CoRR abs/2406.12589 (2024) - 2023
- [c7]Halil Yigit Öksüz, Fabio Molinari, Henning Sprekeler, Jörg Raisch:
Federated Learning in Wireless Networks via Over-the-Air Computations. CDC 2023: 4379-4386 - [c6]Robert Tjarko Lange, Henning Sprekeler
:
Lottery tickets in evolutionary optimization: On sparse backpropagation-free trainability. GECCO Companion 2023: 31-32 - [c5]Robert Tjarko Lange, Henning Sprekeler:
Lottery Tickets in Evolutionary Optimization: On Sparse Backpropagation-Free Trainability. ICML 2023: 18535-18547 - [i5]Halil Yigit Öksüz, Fabio Molinari, Henning Sprekeler, Jörg Raisch:
Federated Learning in Wireless Networks via Over-the-Air Computations. CoRR abs/2305.04630 (2023) - [i4]Robert Tjarko Lange, Henning Sprekeler:
Lottery Tickets in Evolutionary Optimization: On Sparse Backpropagation-Free Trainability. CoRR abs/2306.00045 (2023) - 2022
- [j19]Denis Alevi, Marcel Stimberg
, Henning Sprekeler, Klaus Obermayer, Moritz Augustin
:
Brian2CUDA: Flexible and Efficient Simulation of Spiking Neural Network Models on GPUs. Frontiers Neuroinformatics 16 (2022) - [j18]Joram Keijser
, Henning Sprekeler
:
Optimizing interneuron circuits for compartment-specific feedback inhibition. PLoS Comput. Biol. 18(4) (2022) - [c4]Robert Tjarko Lange, Henning Sprekeler:
Learning Not to Learn: Nature versus Nurture In Silico. AAAI 2022: 7290-7299 - [c3]Marc Aurel Vischer, Robert Tjarko Lange, Henning Sprekeler:
On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning. ICLR 2022 - [i3]Peter Udo Diehl, Yosef Singer, Hannes Zilly, Uwe Schönfeld, Paul Meyer-Rachner, Mark Berry, Henning Sprekeler, Elias Sprengel, Annett Pudszuhn, Veit M. Hofmann:
Restoring speech intelligibility for hearing aid users with deep learning. CoRR abs/2206.11567 (2022) - 2021
- [j17]Filip Vercruysse
, Richard Naud
, Henning Sprekeler
:
Self-organization of a doubly asynchronous irregular network state for spikes and bursts. PLoS Comput. Biol. 17(11) (2021) - [j16]Michiel W. H. Remme
, Urs Bergmann
, Denis Alevi
, Susanne Schreiber
, Henning Sprekeler
, Richard Kempter
:
Hebbian plasticity in parallel synaptic pathways: A circuit mechanism for systems memory consolidation. PLoS Comput. Biol. 17(12) (2021) - [i2]Marc Aurel Vischer, Robert Tjarko Lange, Henning Sprekeler:
On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning. CoRR abs/2105.01648 (2021) - 2020
- [j15]Laura Bella Naumann
, Henning Sprekeler
:
Presynaptic inhibition rapidly stabilises recurrent excitation in the face of plasticity. PLoS Comput. Biol. 16(8) (2020) - [i1]Robert Tjarko Lange, Henning Sprekeler:
Learning not to learn: Nature versus nurture in silico. CoRR abs/2010.04466 (2020)
2010 – 2019
- 2019
- [j14]Simon N. Weber
, Henning Sprekeler
:
A local measure of symmetry and orientation for individual spikes of grid cells. PLoS Comput. Biol. 15(2) (2019) - [j13]Loreen Hertäg
, Henning Sprekeler
:
Amplifying the redistribution of somato-dendritic inhibition by the interplay of three interneuron types. PLoS Comput. Biol. 15(5) (2019) - 2017
- [j12]Nikolay Chenkov, Henning Sprekeler
, Richard Kempter:
Memory replay in balanced recurrent networks. PLoS Comput. Biol. 13(1) (2017) - 2016
- [j11]Katharina A. Wilmes
, Henning Sprekeler
, Susanne Schreiber:
Inhibition as a Binary Switch for Excitatory Plasticity in Pyramidal Neurons. PLoS Comput. Biol. 12(3) (2016) - 2015
- [j10]Tiziano D'Albis, Jorge Jaramillo
, Henning Sprekeler
, Richard Kempter:
Inheritance of Hippocampal Place Fields Through Hebbian Learning: Effects of Theta Modulation and Phase Precession on Structure Formation. Neural Comput. 27(8): 1624-1672 (2015) - 2014
- [j9]Henning Sprekeler, Tiziano Zito, Laurenz Wiskott:
An extension of slow feature analysis for nonlinear blind source separation. J. Mach. Learn. Res. 15(1): 921-947 (2014) - [c2]Erik M. Rehn
, Henning Sprekeler
:
Nonlinear Supervised Locality Preserving Projections for Visual Pattern Discrimination. ICPR 2014: 1568-1573 - 2013
- [j8]Nicolas Frémaux, Henning Sprekeler
, Wulfram Gerstner
:
Reinforcement Learning Using a Continuous Time Actor-Critic Framework with Spiking Neurons. PLoS Comput. Biol. 9(4) (2013) - 2012
- [j7]Johannes Rüter, Nicolas Marcille, Henning Sprekeler
, Wulfram Gerstner
, Michael H. Herzog
:
Paradoxical Evidence Integration in Rapid Decision Processes. PLoS Comput. Biol. 8(2) (2012) - 2011
- [j6]Henning Sprekeler
, Laurenz Wiskott
:
A Theory of Slow Feature Analysis for Transformation-Based Input Signals with an Application to Complex Cells. Neural Comput. 23(2): 303-335 (2011) - [j5]Henning Sprekeler
:
On the Relation of Slow Feature Analysis and Laplacian Eigenmaps. Neural Comput. 23(12): 3287-3302 (2011) - [j4]Laurenz Wiskott
, Pietro Berkes
, Mathias Franzius, Henning Sprekeler, Niko Wilbert:
Slow feature analysis. Scholarpedia 6(4): 5282 (2011)
2000 – 2009
- 2009
- [c1]Henning Sprekeler, Guillaume Hennequin, Wulfram Gerstner:
Code-specific policy gradient rules for spiking neurons. NIPS 2009: 1741-1749 - 2008
- [j3]Felix Creutzig, Henning Sprekeler
:
Predictive Coding and the Slowness Principle: An Information-Theoretic Approach. Neural Comput. 20(4): 1026-1041 (2008) - 2007
- [j2]Henning Sprekeler
, Christian Michaelis, Laurenz Wiskott
:
Slowness: An Objective for Spike-Timing-Dependent Plasticity? PLoS Comput. Biol. 3(6) (2007) - [j1]Mathias Franzius, Henning Sprekeler
, Laurenz Wiskott
:
Slowness and Sparseness Lead to Place, Head-Direction, and Spatial-View Cells. PLoS Comput. Biol. 3(8) (2007)
Coauthor Index
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last updated on 2024-07-15 01:04 CEST by the dblp team
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