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
NEST 2.12. 0
S Kunkel, A Morrison, P Weidel, JM Eppler, A Sinha, W Schenck
Zenodo doi 10, 2017
Evolving interpretable plasticity for spiking networks
J Jordan, M Schmidt, W Senn, MA Petrovici
Elife 10, e66273, 2021
NEST 2.18. 0
J Jordan, R Deepu, J Mitchell, JM Eppler, S Spreizer, J Hahne, ...
Jülich Supercomputing Center, 2019
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
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
NEST 2.20. 0
T Fardet, R Deepu, J Mitchell, JM Eppler, S Spreizer, J Hahne, I Kitayama, ...
Computational and Systems Neuroscience, 2020
NEST 2.14. 0
A Peyser, A Sinha, SB Vennemo, T Ippen, J Jordan, S Graber, A Morrison, ...
Zenodo, 2017
Deterministic networks for probabilistic computing
J Jordan, MA Petrovici, O Breitwieser, J Schemmel, K Meier, M Diesmann, ...
Scientific Reports 9 (1), 1-17, 2019
Learning cortical representations through perturbed and adversarial dreaming
N Deperrois, MA Petrovici, W Senn, J Jordan
Elife 11, e76384, 2022
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
NEST 2.16. 0
C Linssen, R Deepu, J Mitchell, ME Lepperød, J Garrido, S Spreizer, ...
Jülich Supercomputing Center, 2018
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
NEST 3.0
J Hahne, S Diaz, A Patronis, W Schenck, A Peyser, S Graber, S Spreizer, ...
Zenedo. doi 10, 2021
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
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
Parallel Computing 113, 102952, 2022
NEST 3.3
S Spreizer, J Mitchell, J Jordan, W Wybo, A Kurth, SB Vennemo, J Pronold, ...
Version, 2022
A Modular Workflow for Performance Benchmarking of Neuronal Network Simulations
J Albers, J Pronold, AC Kurth, SB Vennemo, KH Mood, A Patronis, ...
Frontiers in neuroinformatics 16, 2022
NEST 2.8. 0
JM Eppler, R Deepu, C Bachmann, T Zito, A Peyser, J Jordan, R Pauli, ...
JARA-HPC, 2015
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
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Articles 1–20