David Kappel

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Citations	1172	1003
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Wolfgang MaassProfessor of Computer Science, Graz University of TechnologyVerified email at igi.tugraz.at
Robert LegensteinInstitute for Theoretical Computer Science, Graz University of TechnologyVerified email at igi.tugraz.at
Christian MayrProfessor, Technische Universität DresdenVerified email at tu-dresden.de
Bernhard VoggingerTechnische Universität DresdenVerified email at tu-dresden.de
Anand SubramoneyRoyal Holloway, University of LondonVerified email at rhul.ac.uk
Guillaume BELLECEPFLVerified email at epfl.ch
Erika CoviZernike Institute for Advanced Materials & CogniGron Center, University of GroningenVerified email at rug.nl
Johannes PartzschChair for Highly Parallel VLSI Systems and Neuromorphic Circuits, TU DresdenVerified email at tu-dresden.de
Univ.-Prof. Dr. Elmar RueckertChair of Cyber-Physical-Systems at Montanuniversität LeobenVerified email at ai-lab.science
Bernhard NesslerSCCH GmbH & Johannes Kepler University Linz, AustriaVerified email at scch.at
Steve FurberProfessor Emeritus, Department of Computer Science, The University of Manchester, UKVerified email at manchester.ac.uk
Jan PetersProfessor for Intelligent Autonomous Systems/TU Darmstadt, Dept. Head/German AI Research Center DFKIVerified email at ias.tu-darmstadt.de
Dr. Christian TetzlaffUniversity Medical Center GöttingenVerified email at med.uni-goettingen.de
Hadi HeidariProfessor of Nanoelectronics, James Watt School of Engineering, University of GlasgowVerified email at glasgow.ac.uk
Melika PayvandAssistant Professor at Institute of Neuroinformatics, UZH and ETH ZurichVerified email at ini.uzh.ch
Elisa DonatiScientist at INI, Institute of Neuroinformatics, UZH/ETHVerified email at ini.uzh.ch
Jacques KaiserDeepScenarioVerified email at deepscenario.com
Sen SongLaboratory of Brain and Intelligence, Dept of Biomedical Engineering, Tsinghua University

David Kappel

Ruhr-Universität Bochum

Verified email at rub.de

computational neuroscience machine learning neuromorphic engineering


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Deep rewiring: Training very sparse deep networks G Bellec, D Kappel, W Maass, R Legenstein arXiv preprint arXiv:1711.05136, 2017	311	2017
Network plasticity as Bayesian inference D Kappel, S Habenschuss, R Legenstein, W Maass PLoS computational biology 11 (11), e1004485, 2015	140	2015
STDP installs in winner-take-all circuits an online approximation to hidden Markov model learning D Kappel, B Nessler, W Maass PLoS computational biology 10 (3), e1003511, 2014	131	2014
Adaptive extreme edge computing for wearable devices E Covi, E Donati, X Liang, D Kappel, H Heidari, M Payvand, W Wang Frontiers in Neuroscience 15, 611300, 2021	120	2021
Recurrent spiking networks solve planning tasks E Rueckert, D Kappel, D Tanneberg, D Pecevski, J Peters Scientific reports 6 (1), 21142, 2016	84	2016
Memory-efficient deep learning on a SpiNNaker 2 prototype C Liu, G Bellec, B Vogginger, D Kappel, J Partzsch, F Neumärker, ... Frontiers in neuroscience 12, 840, 2018	69	2018
A dynamic connectome supports the emergence of stable computational function of neural circuits through reward-based learning D Kappel, R Legenstein, S Habenschuss, M Hsieh, W Maass eneuro 5 (2), 2018	62	2018
Efficient reward-based structural plasticity on a SpiNNaker 2 prototype Y Yan, D Kappel, F Neumärker, J Partzsch, B Vogginger, S Höppner, ... IEEE transactions on biomedical circuits and systems 13 (3), 579-591, 2019	46	2019
Structural plasticity on an accelerated analog neuromorphic hardware system S Billaudelle, B Cramer, MA Petrovici, K Schreiber, D Kappel, ... Neural Networks 133, 11-20, 2021	28	2021
Synaptic sampling: A Bayesian approach to neural network plasticity and rewiring D Kappel, S Habenschuss, R Legenstein, W Maass Advances in neural information processing systems 28, 2015	28	2015
NEVESIM: event-driven neural simulation framework with a Python interface D Pecevski, D Kappel, Z Jonke Frontiers in neuroinformatics 8, 70, 2014	26	2014
NEST 2.14. 0 A Peyser, R Deepu, J Mitchell, S Appukuttan, T Schumann, JM Eppler, ... Jülich Supercomputing Center, 2017	24	2017
Attention on abstract visual reasoning L Hahne, T Lüddecke, F Wörgötter, D Kappel arXiv preprint arXiv:1911.05990, 2019	22	2019
Embodied synaptic plasticity with online reinforcement learning J Kaiser, M Hoff, A Konle, JC Vasquez Tieck, D Kappel, D Reichard, ... Frontiers in Neurorobotics 13, 81, 2019	18	2019
Efficient recurrent architectures through activity sparsity and sparse back-propagation through time A Subramoney, KK Nazeer, M Schöne, C Mayr, D Kappel The Eleventh International Conference on Learning Representations, 2023	16	2023
Reward-based stochastic self-configuration of neural circuits D Kappel, R Legenstein, S Habenschuss, M Hsieh, W Maass arXiv preprint arXiv:1704.04238, 1162-1167, 2017	10	2017
Event-based neural network for ECG classification with delta encoding and early stopping M Jobst, C Liu, J Partzsch, Y Yan, D Kappel, HA Gonzalez, Y Ji, ... 2020 6th International Conference on Event-Based Control, Communication, and …, 2020	7	2020
CaMKII activation supports reward-based neural network optimization through Hamiltonian sampling Z Yu, D Kappel, R Legenstein, S Song, F Chen, W Maass arXiv preprint arXiv:1606.00157, 2016	7	2016
CoBeL-RL: A neuroscience-oriented simulation framework for complex behavior and learning N Diekmann, S Vijayabaskaran, X Zeng, D Kappel, MC Menezes, ... Frontiers in Neuroinformatics 17, 1134405, 2023	4	2023
Language Modeling on a SpiNNaker2 Neuromorphic Chip KK Nazeer, M Schöne, R Mukherji, B Vogginger, C Mayr, D Kappel, ... 2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS …, 2024	3	2024

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