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Promises and pitfalls of deep neural networks in neuroimaging-based
  psychiatric research

Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research

20 January 2023
Fabian Eitel
Marc-Andre Schulz
Moritz Seiler
Henrik Walter
K. Ritter
    AI4CE
ArXivPDFHTML

Papers citing "Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric research"

6 / 6 papers shown
Title
Thermodynamics of learning physical phenomena
Thermodynamics of learning physical phenomena
Elías Cueto
Francisco Chinesta
AI4CE
23
22
0
26 Jul 2022
Label scarcity in biomedicine: Data-rich latent factor discovery
  enhances phenotype prediction
Label scarcity in biomedicine: Data-rich latent factor discovery enhances phenotype prediction
Marc-Andre Schulz
B. Thirion
Alexandre Gramfort
Gaël Varoquaux
D. Bzdok
34
1
0
12 Oct 2021
A Survey on Deep Learning in Medical Image Analysis
A Survey on Deep Learning in Medical Image Analysis
G. Litjens
Thijs Kooi
B. Bejnordi
A. Setio
F. Ciompi
Mohsen Ghafoorian
Jeroen van der Laak
Bram van Ginneken
C. I. Sánchez
OOD
283
10,613
0
19 Feb 2017
Geometric deep learning: going beyond Euclidean data
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
247
3,236
0
24 Nov 2016
The Loss Surfaces of Multilayer Networks
The Loss Surfaces of Multilayer Networks
A. Choromańska
Mikael Henaff
Michaël Mathieu
Gerard Ben Arous
Yann LeCun
ODL
179
1,185
0
30 Nov 2014
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomáš Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
233
31,253
0
16 Jan 2013
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