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| 001 | 1005203 | ||
| 005 | 20240313095025.0 | ||
| 024 | 7 | _ | |a 10.5281/ZENODO.7648959 |2 doi |
| 037 | _ | _ | |a FZJ-2023-01370 |
| 100 | 1 | _ | |a Linssen, Charl |0 P:(DE-Juel1)176305 |b 0 |e Corresponding author |u fzj |
| 245 | _ | _ | |a NESTML 5.2.0 |
| 260 | _ | _ | |c 2023 |
| 336 | 7 | _ | |a Software |2 DCMI |
| 336 | 7 | _ | |a Software |b sware |m sware |0 PUB:(DE-HGF)33 |s 1677738387_7568 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a MISC |2 BibTeX |
| 336 | 7 | _ | |a Computer Program |0 6 |2 EndNote |
| 336 | 7 | _ | |a OTHER |2 ORCID |
| 336 | 7 | _ | |a Software |2 DataCite |
| 520 | _ | _ | |a NESTML 5.2.0 contains many fixes, enhancements in user experience, and documentation updates. Add support for NEST 3.4 Support vector input ports in differential equations Made input ports more consistent in formulation and easier to use Allow solver selection of numeric vs. analytic solver in NEST code generator Compile NESTML generated code multithreaded Allow Node parameters and state variables to be assigned NEST probability distributions Add spike-frequency adaptation tutorial to the documentation For further information, please visit https://github.com/nest/nestml . |
| 536 | _ | _ | |a 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511) |0 G:(DE-HGF)POF4-5111 |c POF4-511 |f POF IV |x 0 |
| 536 | _ | _ | |a 5234 - Emerging NC Architectures (POF4-523) |0 G:(DE-HGF)POF4-5234 |c POF4-523 |f POF IV |x 1 |
| 536 | _ | _ | |a 5235 - Digitization of Neuroscience and User-Community Building (POF4-523) |0 G:(DE-HGF)POF4-5235 |c POF4-523 |f POF IV |x 2 |
| 536 | _ | _ | |a 5232 - Computational Principles (POF4-523) |0 G:(DE-HGF)POF4-5232 |c POF4-523 |f POF IV |x 3 |
| 536 | _ | _ | |a HBP SGA1 - Human Brain Project Specific Grant Agreement 1 (720270) |0 G:(EU-Grant)720270 |c 720270 |f H2020-Adhoc-2014-20 |x 4 |
| 536 | _ | _ | |a HBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907) |0 G:(EU-Grant)785907 |c 785907 |f H2020-SGA-FETFLAG-HBP-2017 |x 5 |
| 536 | _ | _ | |a HBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539) |0 G:(EU-Grant)945539 |c 945539 |f H2020-SGA-FETFLAG-HBP-2019 |x 6 |
| 536 | _ | _ | |a SLNS - SimLab Neuroscience (Helmholtz-SLNS) |0 G:(DE-Juel1)Helmholtz-SLNS |c Helmholtz-SLNS |x 7 |
| 536 | _ | _ | |a PhD no Grant - Doktorand ohne besondere Förderung (PHD-NO-GRANT-20170405) |0 G:(DE-Juel1)PHD-NO-GRANT-20170405 |c PHD-NO-GRANT-20170405 |x 8 |
| 588 | _ | _ | |a Dataset connected to DataCite |
| 700 | 1 | _ | |a Babu, Pooja |0 P:(DE-Juel1)186954 |b 1 |u fzj |
| 700 | 1 | _ | |a Benelhedi, Mohamed Ayssar |0 P:(DE-Juel1)190223 |b 2 |u fzj |
| 700 | 1 | _ | |a Vogelsang, Jan |0 P:(DE-Juel1)173676 |b 3 |u fzj |
| 700 | 1 | _ | |a Fischer, Angela |0 P:(DE-Juel1)191265 |b 4 |u fzj |
| 700 | 1 | _ | |a Eppler, Jochen Martin |0 P:(DE-Juel1)142538 |b 5 |u fzj |
| 700 | 1 | _ | |a Rumpe, Bernhard |0 P:(DE-HGF)0 |b 6 |
| 700 | 1 | _ | |a Morrison, Abigail |0 P:(DE-Juel1)151166 |b 7 |u fzj |
| 773 | _ | _ | |a 10.5281/ZENODO.7648959 |
| 856 | 4 | _ | |u https://doi.org/10.5281/zenodo.7648959 |
| 909 | C | O | |o oai:juser.fz-juelich.de:1005203 |p openaire |p VDB |p ec_fundedresources |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)176305 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 1 |6 P:(DE-Juel1)186954 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 2 |6 P:(DE-Juel1)190223 |
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| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 7 |6 P:(DE-Juel1)151166 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action |1 G:(DE-HGF)POF4-510 |0 G:(DE-HGF)POF4-511 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Enabling Computational- & Data-Intensive Science and Engineering |9 G:(DE-HGF)POF4-5111 |x 0 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Natural, Artificial and Cognitive Information Processing |1 G:(DE-HGF)POF4-520 |0 G:(DE-HGF)POF4-523 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Neuromorphic Computing and Network Dynamics |9 G:(DE-HGF)POF4-5234 |x 1 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Natural, Artificial and Cognitive Information Processing |1 G:(DE-HGF)POF4-520 |0 G:(DE-HGF)POF4-523 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Neuromorphic Computing and Network Dynamics |9 G:(DE-HGF)POF4-5235 |x 2 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Natural, Artificial and Cognitive Information Processing |1 G:(DE-HGF)POF4-520 |0 G:(DE-HGF)POF4-523 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Neuromorphic Computing and Network Dynamics |9 G:(DE-HGF)POF4-5232 |x 3 |
| 914 | 1 | _ | |y 2023 |
| 920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-6-20090406 |k INM-6 |l Computational and Systems Neuroscience |x 1 |
| 920 | 1 | _ | |0 I:(DE-Juel1)IAS-6-20130828 |k IAS-6 |l Theoretical Neuroscience |x 2 |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-10-20170113 |k INM-10 |l Jara-Institut Brain structure-function relationships |x 3 |
| 980 | _ | _ | |a sware |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
| 980 | _ | _ | |a I:(DE-Juel1)INM-6-20090406 |
| 980 | _ | _ | |a I:(DE-Juel1)IAS-6-20130828 |
| 980 | _ | _ | |a I:(DE-Juel1)INM-10-20170113 |
| 980 | _ | _ | |a UNRESTRICTED |
| 981 | _ | _ | |a I:(DE-Juel1)IAS-6-20130828 |
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