001033605 001__ 1033605 001033605 005__ 20241213210708.0 001033605 037__ $$aFZJ-2024-06485 001033605 041__ $$aEnglish 001033605 1001_ $$0P:(DE-Juel1)170068$$aSchiffer, Christian$$b0$$ufzj 001033605 1112_ $$aINM Retreat 2024$$cJülich$$d2024-11-19 - 2024-11-19$$wGermany 001033605 245__ $$aTutorial: Deep Learning for Neuroscience 001033605 260__ $$c2024 001033605 3367_ $$2DRIVER$$alecture 001033605 3367_ $$031$$2EndNote$$aGeneric 001033605 3367_ $$2BibTeX$$aMISC 001033605 3367_ $$0PUB:(DE-HGF)17$$2PUB:(DE-HGF)$$aLecture$$blecture$$mlecture$$s1734090846_7859$$xOutreach 001033605 3367_ $$2ORCID$$aLECTURE_SPEECH 001033605 3367_ $$2DataCite$$aText 001033605 520__ $$aMachine Learning – in particular deep learning – has become an indispensable tool for analyzing large neuroscience datasets. The Helmholtz AI team at Jülich is closely connected to these developments and supports research activities at the intersection of AI, high-performance computing (HPC) and neuroscience. Many of the methods and solutions are not limited to neuroscience and medical applications, but can be transferred to different tasks and scientific domains.This tutorial we will give an overview of state-of-the-art deep learning methods in the context of biomedical image analysis and show concrete examples in INM where deep learning already supports neuroscientists in analyzing their data. The second part of this tutorial will offer a hands-on course on how to bring deep learning pipelines on JSC’s HPC systems. 001033605 536__ $$0G:(DE-HGF)POF4-5254$$a5254 - Neuroscientific Data Analytics and AI (POF4-525)$$cPOF4-525$$fPOF IV$$x0 001033605 536__ $$0G:(DE-Juel-1)E.40401.62$$aHelmholtz AI - Helmholtz Artificial Intelligence Coordination Unit – Local Unit FZJ (E.40401.62)$$cE.40401.62$$x1 001033605 536__ $$0G:(DE-HGF)InterLabs-0015$$aHIBALL - Helmholtz International BigBrain Analytics and Learning Laboratory (HIBALL) (InterLabs-0015)$$cInterLabs-0015$$x2 001033605 536__ $$0G:(DE-HGF)ZT-I-PF-4-061$$aX-BRAIN (ZT-I-PF-4-061)$$cZT-I-PF-4-061$$x3 001033605 7001_ $$0P:(DE-Juel1)165746$$aDickscheid, Timo$$b1$$ufzj 001033605 7001_ $$0P:(DE-Juel1)192312$$aBenassou, Sabrina$$b2$$ufzj 001033605 7001_ $$0P:(DE-Juel1)206762$$aKasravi, Javad$$b3$$ufzj 001033605 7001_ $$0P:(DE-Juel1)140202$$aStrube, Alexandre$$b4$$ufzj 001033605 909CO $$ooai:juser.fz-juelich.de:1033605$$pVDB 001033605 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)170068$$aForschungszentrum Jülich$$b0$$kFZJ 001033605 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)165746$$aForschungszentrum Jülich$$b1$$kFZJ 001033605 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)192312$$aForschungszentrum Jülich$$b2$$kFZJ 001033605 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)206762$$aForschungszentrum Jülich$$b3$$kFZJ 001033605 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)140202$$aForschungszentrum Jülich$$b4$$kFZJ 001033605 9131_ $$0G:(DE-HGF)POF4-525$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5254$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vDecoding Brain Organization and Dysfunction$$x0 001033605 9141_ $$y2024 001033605 920__ $$lyes 001033605 9201_ $$0I:(DE-Juel1)INM-1-20090406$$kINM-1$$lStrukturelle und funktionelle Organisation des Gehirns$$x0 001033605 980__ $$alecture 001033605 980__ $$aVDB 001033605 980__ $$aI:(DE-Juel1)INM-1-20090406 001033605 980__ $$aUNRESTRICTED