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Self-supervised multimodal neuroimaging yields predictive
  representations for a spectrum of Alzheimer's phenotypes

Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes

7 September 2022
A. Fedorov
Eloy P. T. Geenjaar
Lei Wu
Tristan Sylvain
T. DeRamus
Margaux Luck
Maria B. Misiura
R. Devon Hjelm
Sergey Plis
Vince D. Calhoun
ArXiv (abs)PDFHTML

Papers citing "Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes"

50 / 52 papers shown
Title
Drop, Swap, and Generate: A Self-Supervised Approach for Generating
  Neural Activity
Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity
Ran Liu
Mehdi Azabou
M. Dabagia
Chi-Heng Lin
M. G. Azar
Keith B. Hengen
Michal Valko
Eva L. Dyer
OCLSSLDRL
39
37
0
03 Nov 2021
Understanding Latent Correlation-Based Multiview Learning and
  Self-Supervision: An Identifiability Perspective
Understanding Latent Correlation-Based Multiview Learning and Self-Supervision: An Identifiability Perspective
Qinjie Lyu
Xiao Fu
Weiran Wang
Songtao Lu
SSL
60
31
0
14 Jun 2021
Self-Supervised Learning with Data Augmentations Provably Isolates
  Content from Style
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
Julius von Kügelgen
Yash Sharma
Luigi Gresele
Wieland Brendel
Bernhard Schölkopf
M. Besserve
Francesco Locatello
99
317
0
08 Jun 2021
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Alec Radford
Jong Wook Kim
Chris Hallacy
Aditya A. Ramesh
Gabriel Goh
...
Amanda Askell
Pamela Mishkin
Jack Clark
Gretchen Krueger
Ilya Sutskever
CLIPVLM
967
29,810
0
26 Feb 2021
Self-Supervised Multimodal Domino: in Search of Biomarkers for
  Alzheimer's Disease
Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease
A. Fedorov
Tristan Sylvain
Eloy P. T. Geenjaar
Margaux Luck
Lei Wu
T. DeRamus
Alex Kirilin
Dmitry Bleklov
Vince D. Calhoun
Sergey Plis
SSL
54
13
0
25 Dec 2020
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural
  Network Representations Vary with Width and Depth
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth
Thao Nguyen
M. Raghu
Simon Kornblith
OOD
62
282
0
29 Oct 2020
Zero-Shot Learning from scratch (ZFS): leveraging local compositional
  representations
Zero-Shot Learning from scratch (ZFS): leveraging local compositional representations
Tristan Sylvain
Linda Petrini
R. Devon Hjelm
VLM
37
7
0
22 Oct 2020
Whole MILC: generalizing learned dynamics across tasks, datasets, and
  populations
Whole MILC: generalizing learned dynamics across tasks, datasets, and populations
Usman Mahmood
Md. Mahfuzur Rahman
A. Fedorov
N. Lewis
Z. Fu
Vince D. Calhoun
Sergey Plis
49
22
0
29 Jul 2020
Self-Supervised MultiModal Versatile Networks
Self-Supervised MultiModal Versatile Networks
Jean-Baptiste Alayrac
Adrià Recasens
R. Schneider
Relja Arandjelović
Jason Ramapuram
J. Fauw
Lucas Smaira
Sander Dieleman
Andrew Zisserman
SSL
139
375
0
29 Jun 2020
Unsupervised Learning of Visual Features by Contrasting Cluster
  Assignments
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
Mathilde Caron
Ishan Misra
Julien Mairal
Priya Goyal
Piotr Bojanowski
Armand Joulin
OCLSSL
261
4,098
0
17 Jun 2020
3D Self-Supervised Methods for Medical Imaging
3D Self-Supervised Methods for Medical Imaging
Aiham Taleb
W. Loetzsch
Noel Danz
Julius Severin
Thomas Gaertner
Benjamin Bergner
C. Lippert
SSL
101
214
0
06 Jun 2020
Shortcut Learning in Deep Neural Networks
Shortcut Learning in Deep Neural Networks
Robert Geirhos
J. Jacobsen
Claudio Michaelis
R. Zemel
Wieland Brendel
Matthias Bethge
Felix Wichmann
214
2,059
0
16 Apr 2020
Decision-Making with Auto-Encoding Variational Bayes
Decision-Making with Auto-Encoding Variational Bayes
Romain Lopez
Pierre Boyeau
Nir Yosef
Michael I. Jordan
Jeffrey Regier
BDL
500
10,591
0
17 Feb 2020
A Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual Representations
Ting-Li Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey E. Hinton
SSL
375
18,866
0
13 Feb 2020
Locality and compositionality in zero-shot learning
Locality and compositionality in zero-shot learning
Tristan Sylvain
Linda Petrini
R. Devon Hjelm
55
56
0
20 Dec 2019
End-to-End Learning of Visual Representations from Uncurated
  Instructional Videos
End-to-End Learning of Visual Representations from Uncurated Instructional Videos
Antoine Miech
Jean-Baptiste Alayrac
Lucas Smaira
Ivan Laptev
Josef Sivic
Andrew Zisserman
VGenSSL
128
713
0
13 Dec 2019
Self-Supervised Learning of Pretext-Invariant Representations
Self-Supervised Learning of Pretext-Invariant Representations
Ishan Misra
Laurens van der Maaten
SSLVLM
108
1,458
0
04 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
538
42,591
0
03 Dec 2019
Transfer Learning of fMRI Dynamics
Transfer Learning of fMRI Dynamics
Usman Mahmood
Md. Mahfuzur Rahman
A. Fedorov
Z. Fu
Sergey Plis
32
9
0
16 Nov 2019
Momentum Contrast for Unsupervised Visual Representation Learning
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He
Haoqi Fan
Yuxin Wu
Saining Xie
Ross B. Girshick
SSL
210
12,124
0
13 Nov 2019
FastSurfer -- A fast and accurate deep learning based neuroimaging
  pipeline
FastSurfer -- A fast and accurate deep learning based neuroimaging pipeline
Leonie Henschel
Sailesh Conjeti
Santiago Estrada
K. Diers
Bruce Fischl
M. Reuter
MedIm
102
404
0
09 Oct 2019
On the Variance of the Adaptive Learning Rate and Beyond
On the Variance of the Adaptive Learning Rate and Beyond
Liyuan Liu
Haoming Jiang
Pengcheng He
Weizhu Chen
Xiaodong Liu
Jianfeng Gao
Jiawei Han
ODL
289
1,907
0
08 Aug 2019
On Mutual Information Maximization for Representation Learning
On Mutual Information Maximization for Representation Learning
Michael Tschannen
Josip Djolonga
Paul Kishan Rubenstein
Sylvain Gelly
Mario Lucic
SSL
179
501
0
31 Jul 2019
Optuna: A Next-generation Hyperparameter Optimization Framework
Optuna: A Next-generation Hyperparameter Optimization Framework
Takuya Akiba
Shotaro Sano
Toshihiko Yanase
Takeru Ohta
Masanori Koyama
666
5,839
0
25 Jul 2019
Using Self-Supervised Learning Can Improve Model Robustness and
  Uncertainty
Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty
Dan Hendrycks
Mantas Mazeika
Saurav Kadavath
Basel Alomair
OODSSL
56
948
0
28 Jun 2019
Unsupervised State Representation Learning in Atari
Unsupervised State Representation Learning in Atari
Ankesh Anand
Evan Racah
Sherjil Ozair
Yoshua Bengio
Marc-Alexandre Côté
R. Devon Hjelm
SSL
66
255
0
19 Jun 2019
Contrastive Multiview Coding
Contrastive Multiview Coding
Yonglong Tian
Dilip Krishnan
Phillip Isola
SSL
174
2,409
0
13 Jun 2019
Learning Representations by Maximizing Mutual Information Across Views
Learning Representations by Maximizing Mutual Information Across Views
Philip Bachman
R. Devon Hjelm
William Buchwalter
SSL
195
1,477
0
03 Jun 2019
Putting An End to End-to-End: Gradient-Isolated Learning of
  Representations
Putting An End to End-to-End: Gradient-Isolated Learning of Representations
Sindy Löwe
Peter O'Connor
Bastiaan S. Veeling
SSL
117
144
0
28 May 2019
Data-Efficient Image Recognition with Contrastive Predictive Coding
Data-Efficient Image Recognition with Contrastive Predictive Coding
Olivier J. Hénaff
A. Srinivas
J. Fauw
Ali Razavi
Carl Doersch
S. M. Ali Eslami
Aaron van den Oord
SSL
138
1,432
0
22 May 2019
Similarity of Neural Network Representations Revisited
Similarity of Neural Network Representations Revisited
Simon Kornblith
Mohammad Norouzi
Honglak Lee
Geoffrey E. Hinton
143
1,431
0
01 May 2019
Prediction of Progression to Alzheimer's disease with Deep InfoMax
Prediction of Progression to Alzheimer's disease with Deep InfoMax
A. Fedorov
R. Devon Hjelm
A. Abrol
Z. Fu
Yuhui Du
Sergey Plis
Vince D. Calhoun
MedIm
24
23
0
24 Apr 2019
Learning deep representations by mutual information estimation and
  maximization
Learning deep representations by mutual information estimation and maximization
R. Devon Hjelm
A. Fedorov
Samuel Lavoie-Marchildon
Karan Grewal
Phil Bachman
Adam Trischler
Yoshua Bengio
SSLDRL
335
2,672
0
20 Aug 2018
Representation Learning with Contrastive Predictive Coding
Representation Learning with Contrastive Predictive Coding
Aaron van den Oord
Yazhe Li
Oriol Vinyals
DRLSSL
351
10,356
0
10 Jul 2018
Insights on representational similarity in neural networks with
  canonical correlation
Insights on representational similarity in neural networks with canonical correlation
Ari S. Morcos
M. Raghu
Samy Bengio
DRL
68
447
0
14 Jun 2018
Unsupervised Representation Learning by Predicting Image Rotations
Unsupervised Representation Learning by Predicting Image Rotations
Spyros Gidaris
Praveer Singh
N. Komodakis
OODSSLDRL
263
3,298
0
21 Mar 2018
Almost instant brain atlas segmentation for large-scale studies
Almost instant brain atlas segmentation for large-scale studies
A. Fedorov
Eswar Damaraju
Vince D. Calhoun
Sergey Plis
47
13
0
01 Nov 2017
A Closer Look at Memorization in Deep Networks
A Closer Look at Memorization in Deep Networks
Devansh Arpit
Stanislaw Jastrzebski
Nicolas Ballas
David M. Krueger
Emmanuel Bengio
...
Tegan Maharaj
Asja Fischer
Aaron Courville
Yoshua Bengio
Simon Lacoste-Julien
TDI
128
1,825
0
16 Jun 2017
Multimodal Machine Learning: A Survey and Taxonomy
Multimodal Machine Learning: A Survey and Taxonomy
T. Baltrušaitis
Chaitanya Ahuja
Louis-Philippe Morency
111
2,937
0
26 May 2017
In Defense of the Triplet Loss for Person Re-Identification
In Defense of the Triplet Loss for Person Re-Identification
Alexander Hermans
Lucas Beyer
Bastian Leibe
DML
105
3,210
0
22 Mar 2017
Axiomatic Attribution for Deep Networks
Axiomatic Attribution for Deep Networks
Mukund Sundararajan
Ankur Taly
Qiqi Yan
OODFAtt
193
6,018
0
04 Mar 2017
DeMIAN: Deep Modality Invariant Adversarial Network
DeMIAN: Deep Modality Invariant Adversarial Network
Kuniaki Saito
Yusuke Mukuta
Yoshitaka Ushiku
Tatsuya Harada
VLMGAN
33
6
0
23 Dec 2016
End-to-end learning of brain tissue segmentation from imperfect labeling
End-to-end learning of brain tissue segmentation from imperfect labeling
A. Fedorov
Jeremy Johnson
Eswar Damaraju
Alexei Ozerin
Vince D. Calhoun
Sergey Plis
MedIm
47
48
0
03 Dec 2016
Understanding intermediate layers using linear classifier probes
Understanding intermediate layers using linear classifier probes
Guillaume Alain
Yoshua Bengio
FAtt
175
957
0
05 Oct 2016
Colorful Image Colorization
Colorful Image Colorization
Richard Y. Zhang
Phillip Isola
Alexei A. Efros
149
3,532
0
28 Mar 2016
On Deep Multi-View Representation Learning: Objectives and Optimization
On Deep Multi-View Representation Learning: Objectives and Optimization
Weiran Wang
R. Arora
Karen Livescu
J. Bilmes
SSLDRL
90
915
0
02 Feb 2016
Unsupervised Representation Learning with Deep Convolutional Generative
  Adversarial Networks
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Alec Radford
Luke Metz
Soumith Chintala
GANOOD
271
14,023
0
19 Nov 2015
Unsupervised Visual Representation Learning by Context Prediction
Unsupervised Visual Representation Learning by Context Prediction
Carl Doersch
Abhinav Gupta
Alexei A. Efros
DRLSSL
169
2,789
0
19 May 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg3DV
1.9K
77,378
0
18 May 2015
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly
  Convex Composite Objectives
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives
Aaron Defazio
Francis R. Bach
Simon Lacoste-Julien
ODL
135
1,828
0
01 Jul 2014
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