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| 001 | 1052972 | ||
| 005 | 20260128204149.0 | ||
| 024 | 7 | _ | |a 10.5281/ZENODO.17395886 |2 doi |
| 037 | _ | _ | |a FZJ-2026-01322 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |a Fischer, Kirsten |0 P:(DE-Juel1)180150 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Field theory for optimal signal propagation in ResNets |
| 260 | _ | _ | |c 2025 |
| 336 | 7 | _ | |a Software |2 DCMI |
| 336 | 7 | _ | |a Software |b sware |m sware |0 PUB:(DE-HGF)33 |s 1769603305_4882 |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 This repository contains the code accompanying the paper: Fischer, K., Dahmen, D., Helias, M. (2023). Field theory for optimal signal propagation in ResNets (arXiv:2305.07715). For any questions, please contact Kirsten Fischer (ki.fischer@fz-juelich.de). |
| 536 | _ | _ | |a 5231 - Neuroscientific Foundations (POF4-523) |0 G:(DE-HGF)POF4-5231 |c POF4-523 |f POF IV |x 0 |
| 536 | _ | _ | |a 5232 - Computational Principles (POF4-523) |0 G:(DE-HGF)POF4-5232 |c POF4-523 |f POF IV |x 1 |
| 536 | _ | _ | |a RenormalizedFlows - Transparent Deep Learning with Renormalized Flows (BMBF-01IS19077A) |0 G:(DE-Juel-1)BMBF-01IS19077A |c BMBF-01IS19077A |x 2 |
| 536 | _ | _ | |a GRK 2416 - GRK 2416: MultiSenses-MultiScales: Neue Ansätze zur Aufklärung neuronaler multisensorischer Integration (368482240) |0 G:(GEPRIS)368482240 |c 368482240 |x 3 |
| 536 | _ | _ | |a ACA - Advanced Computing Architectures (SO-092) |0 G:(DE-HGF)SO-092 |c SO-092 |x 4 |
| 536 | _ | _ | |a Brain-Scale Simulations (jinb33_20220812) |0 G:(DE-Juel1)jinb33_20220812 |c jinb33_20220812 |f Brain-Scale Simulations |x 5 |
| 536 | _ | _ | |a DFG project G:(GEPRIS)491111487 - Open-Access-Publikationskosten / 2025 - 2027 / Forschungszentrum Jülich (OAPKFZJ) (491111487) |0 G:(GEPRIS)491111487 |c 491111487 |x 6 |
| 588 | _ | _ | |a Dataset connected to DataCite |
| 650 | _ | 7 | |a Field theory |2 Other |
| 650 | _ | 7 | |a Residual networks |2 Other |
| 650 | _ | 7 | |a Machine Learning |2 Other |
| 700 | 1 | _ | |a Dahmen, David |0 P:(DE-Juel1)156459 |b 1 |
| 700 | 1 | _ | |a Helias, Moritz |0 P:(DE-Juel1)144806 |b 2 |
| 773 | _ | _ | |a 10.5281/ZENODO.17395886 |
| 909 | C | O | |o oai:juser.fz-juelich.de:1052972 |p VDB |
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| 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)POF4-5231 |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)POF4-5232 |x 1 |
| 920 | 1 | _ | |0 I:(DE-Juel1)IAS-6-20130828 |k IAS-6 |l Computational and Systems Neuroscience |x 0 |
| 980 | _ | _ | |a sware |
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| 980 | _ | _ | |a UNRESTRICTED |
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