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@MISC{Schiffer:1033605,
author = {Schiffer, Christian and Dickscheid, Timo and Benassou,
Sabrina and Kasravi, Javad and Strube, Alexandre},
title = {{T}utorial: {D}eep {L}earning for {N}euroscience},
reportid = {FZJ-2024-06485},
year = {2024},
abstract = {Machine 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.},
month = {Nov},
date = {2024-11-19},
organization = {INM Retreat 2024, Jülich (Germany),
19 Nov 2024 - 19 Nov 2024},
subtyp = {Outreach},
cin = {INM-1},
cid = {I:(DE-Juel1)INM-1-20090406},
pnm = {5254 - Neuroscientific Data Analytics and AI (POF4-525) /
Helmholtz AI - Helmholtz Artificial Intelligence
Coordination Unit – Local Unit FZJ (E.40401.62) / HIBALL -
Helmholtz International BigBrain Analytics and Learning
Laboratory (HIBALL) (InterLabs-0015) / X-BRAIN
(ZT-I-PF-4-061)},
pid = {G:(DE-HGF)POF4-5254 / G:(DE-Juel-1)E.40401.62 /
G:(DE-HGF)InterLabs-0015 / G:(DE-HGF)ZT-I-PF-4-061},
typ = {PUB:(DE-HGF)17},
url = {https://juser.fz-juelich.de/record/1033605},
}