Jordan, Jakob Jürgen

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Albers, Jasper; Pronold, Jari; Kurth, Anno Christopher; Vennemo, Stine Brekke; Haghighi Mood, Kaveh; Patronis, Alexander; Terhorst, Dennis; Jordan, Jakob; Kunkel, Susanne; Tetzlaff, Tom; Diesmann, Markus; Senk, Johanna (2022). A Modular Workflow for Performance Benchmarking of Neuronal Network Simulations. Frontiers in neuroinformatics, 16, p. 837549. Frontiers Research Foundation 10.3389/fninf.2022.837549

Deperrois, Nicolas; Petrovici, Mihai A; Senn, Walter; Jordan, Jakob (2022). Learning cortical representations through perturbed and adversarial dreaming. eLife, 11 eLife Sciences Publications 10.7554/eLife.76384

Pronold, Jari; Jordan, Jakob; Wylie, Brian J N; Kitayama, Itaru; Diesmann, Markus; Kunkel, Susanne (2022). Routing Brain Traffic Through the Von Neumann Bottleneck: Parallel Sorting and Refactoring. Frontiers in neuroinformatics, 15, p. 785068. Frontiers Research Foundation 10.3389/fninf.2021.785068


Wybo, Willem; Jordan, Jakob; Ellenberger, Benjamin; Marti Mengual, Ulisses; Nevian, Thomas; Senn, Walter (2021). Data-driven reduction of dendritic morphologies with preserved dendro-somatic responses. eLife, 10(e60936) eLife Sciences Publications 10.7554/eLife.60936

Jordan, Jakob; Schmidt, Maximilian; Senn, Walter; Petrovici, Mihai A (2021). Evolving interpretable plasticity for spiking networks. eLife, 10 eLife Sciences Publications 10.7554/eLife.66273

Haider, Paul; Ellenberger, Benjamin; Kriener, Laura; Jordan, Jakob; Senn, Walter; Petrovici, Mihai A. (2021). Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons. Advances in Neural Information Processing Systems (NIPS), 35. MIT Press


Jordan, Jakob Jürgen; Helias, Moritz; Diesmann, Markus; Kunkel, Susanne (2020). Efficient Communication in Distributed Simulations of Spiking Neuronal Networks With Gap Junctions. Frontiers in Neuroinformatics, 14 10.3389/fninf.2020.00012


Jordan, Jakob; Petrovici, Mihai A.; Breitwieser, Oliver; Schemmel, Johannes; Meier, Karlheinz; Diesmann, Markus; Tetzlaff, Tom (2019). Deterministic networks for probabilistic computing. Scientific reports, 9(1), p. 18303. Springer Nature 10.1038/s41598-019-54137-7

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