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Jakob Jordan
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Extremely scalable spiking neural network simulation code: from laptops to exascale computers
J Jordan, T Ippen, M Helias, I Kitayama, M Sato, J Igarashi, M Diesmann, ...
Frontiers in Neuroinformatics 12, 2, 2018
1012018
NEST 2.12. 0
S Kunkel, A Morrison, P Weidel, JM Eppler, A Sinha, W Schenck
Zenodo doi 10, 2017
402017
Effect of Heterogeneity on Decorrelation Mechanisms in Spiking Neural Networks: A Neuromorphic-Hardware Study
T Pfeil, J Jordan, T Tetzlaff, A Grübl, J Schemmel, M Diesmann, K Meier
Physical Review X 6 (2), 021023, 2016
302016
NEST 2.18. 0
J Jordan, R Deepu, J Mitchell, JM Eppler, S Spreizer, J Hahne, ...
Jülich Supercomputing Center, 2019
22*2019
NEST 2.14. 0
A Peyser, A Sinha, SB Vennemo, T Ippen, J Jordan, S Graber, A Morrison, ...
Zenodo, 2017
222017
NEST 2.16. 0
C Linssen, R Deepu, J Mitchell, ME Lepperød, J Garrido, S Spreizer, ...
Jülich Supercomputing Center, 2018
182018
Deterministic networks for probabilistic computing
J Jordan, MA Petrovici, O Breitwieser, J Schemmel, K Meier, M Diesmann, ...
Scientific Reports 9 (1), 1-17, 2019
162019
NEST 2.20. 0
T Fardet, R Deepu, J Mitchell, JM Eppler, S Spreizer, J Hahne, I Kitayama, ...
Computational and Systems Neuroscience, 2020
152020
Data-driven reduction of dendritic morphologies with preserved dendro-somatic responses
WAM Wybo, J Jordan, B Ellenberger, UM Mengual, T Nevian, W Senn
Elife 10, e60936, 2021
112021
Evolving to learn: discovering interpretable plasticity rules for spiking networks
J Jordan, M Schmidt, W Senn, MA Petrovici
arXiv preprint arXiv:2005.14149, 2020
102020
Closing the loop between neural network simulators and the OpenAI Gym
J Jordan, P Weidel, A Morrison
arXiv preprint arXiv:1709.05650, 2017
82017
NEST 2.8. 0
JM Eppler, R Deepu, C Bachmann, T Zito, A Peyser, J Jordan, R Pauli, ...
JARA-HPC, 2015
82015
Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons
P Haider, B Ellenberger, L Kriener, J Jordan, W Senn, MA Petrovici
Thirty-Fifth Conference on Neural Information Processing Systems, 2021
62021
Efficient communication in distributed simulations of spiking neuronal networks with gap junctions
J Jordan, M Helias, M Diesmann, S Kunkel
Frontiers in Neuroinformatics 14, 12, 2020
62020
Stochastic neural computation without noise
J Jordan, MA Petrovici, O Breitwieser, J Schemmel, K Meier, M Diesmann, ...
arXiv preprint arXiv:1710.04931, 2017
52017
Routing brain traffic through the von Neumann bottleneck: Parallel sorting and refactoring
J Pronold, J Jordan, BJN Wylie, I Kitayama, M Diesmann, S Kunkel
Frontiers in neuroinformatics 15, 2021
42021
A closed-loop toolchain for neural network simulations of learning autonomous agents
J Jordan, P Weidel, A Morrison
Frontiers in Computational Neuroscience 13, 46, 2019
42019
Routing brain traffic through the von Neumann bottleneck: Efficient cache usage in spiking neural network simulation code on general purpose computers
J Pronold, J Jordan, BJN Wylie, I Kitayama, M Diesmann, S Kunkel
arXiv preprint arXiv:2109.12855, 2021
22021
Evolving neuronal plasticity rules using cartesian genetic programming
HD Mettler, M Schmidt, W Senn, MA Petrovici, J Jordan
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2021
22021
Conductance-based dendrites perform reliability-weighted opinion pooling
J Jordan, MA Petrovici, W Senn, J Sacramento
Proceedings of the Neuro-inspired Computational Elements Workshop, 1-3, 2020
22020
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