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RobustSleepNet: Transfer learning for automated sleep staging at scale
v1v2 (latest)

RobustSleepNet: Transfer learning for automated sleep staging at scale

IEEE transactions on neural systems and rehabilitation engineering (IEEE TNSRE), 2021
7 January 2021
Antoine Guillot
Valentin Thorey
    OOD
ArXiv (abs)PDFHTML

Papers citing "RobustSleepNet: Transfer learning for automated sleep staging at scale"

19 / 19 papers shown
Bridging Privacy and Utility: Synthesizing anonymized EEG with constraining utility functions
Bridging Privacy and Utility: Synthesizing anonymized EEG with constraining utility functions
Kay Fuhrmeister
Arne Pelzer
Fabian Radke
Julia Lechinger
Mahzad Gharleghi
Thomas Köllmer
Insa Wolf
61
0
0
24 Sep 2025
From Sleep Staging to Spindle Detection: Evaluating End-to-End Automated Sleep Analysis
From Sleep Staging to Spindle Detection: Evaluating End-to-End Automated Sleep Analysis
Niklas Grieger
S. Mehrkanoon
P. Ritter
Stephan Bialonski
306
0
0
08 May 2025
Contrastive random lead coding for channel-agnostic self-supervision of
  biosignals
Contrastive random lead coding for channel-agnostic self-supervision of biosignals
Thea Brusch
Mikkel N. Schmidt
T. S. Alstrøm
SSL
232
0
0
21 Oct 2024
Automatic Classification of Sleep Stages from EEG Signals Using
  Riemannian Metrics and Transformer Networks
Automatic Classification of Sleep Stages from EEG Signals Using Riemannian Metrics and Transformer NetworksSN Computer Science (SCS), 2024
Mathieu Seraphim
Alexis Lechervy
Florian Yger
Luc Brun
Olivier Etard
273
4
0
18 Oct 2024
S4Sleep: Elucidating the design space of deep-learning-based sleep stage classification models
S4Sleep: Elucidating the design space of deep-learning-based sleep stage classification models
Tiezhi Wang
Nils Strodthoff
587
10
0
10 Oct 2023
Structure-Preserving Transformers for Sequences of SPD Matrices
Structure-Preserving Transformers for Sequences of SPD MatricesEuropean Signal Processing Conference (EUSIPCO), 2023
Mathieu Seraphim
Alexis Lechervy
Florian Yger
Luc Brun
Olivier Etard
531
8
0
14 Sep 2023
Multi-view self-supervised learning for multivariate variable-channel
  time series
Multi-view self-supervised learning for multivariate variable-channel time seriesInternational Workshop on Machine Learning for Signal Processing (MLSP), 2023
Thea Brusch
Mikkel N. Schmidt
T. S. Alstrøm
BDLSSLAI4TS
178
8
0
13 Jul 2023
U-PASS: an Uncertainty-guided deep learning Pipeline for Automated Sleep
  Staging
U-PASS: an Uncertainty-guided deep learning Pipeline for Automated Sleep Staging
E. Heremans
Nabeel Seedat
B. Buyse
D. Testelmans
M. Schaar
Marina De Vos
219
9
0
07 Jun 2023
L-SeqSleepNet: Whole-cycle Long Sequence Modelling for Automatic Sleep
  Staging
L-SeqSleepNet: Whole-cycle Long Sequence Modelling for Automatic Sleep StagingIEEE journal of biomedical and health informatics (IEEE JBHI), 2023
Huy P Phan
Kristian P. Lorenzen
E. Heremans
Oliver Y. Chén
Minh C. Tran
P. Koch
Alfred Mertins
M. Baumert
Kaare B. Mikkelsen
Marina De Vos
287
69
0
09 Jan 2023
Modeling Multivariate Biosignals With Graph Neural Networks and
  Structured State Space Models
Modeling Multivariate Biosignals With Graph Neural Networks and Structured State Space ModelsACM Conference on Health, Inference, and Learning (ACM CHIL), 2022
Siyi Tang
Jared A. Dunnmon
Liangqiong Qu
Khaled Kamal Saab
T. Baykaner
Christopher Lee-Messer
D. Rubin
357
43
0
21 Nov 2022
U-Sleep's resilience to AASM guidelines
U-Sleep's resilience to AASM guidelinesnpj Digital Medicine (NDM), 2022
Luigi Fiorillo
Giuliana Monachino
J. van der Meer
M. Pesce
J. Warncke
Markus H. Schmidt
C. Bassetti
A. Tzovara
Paolo Favaro
F. Faraci
328
41
0
19 Sep 2022
Do Not Sleep on Traditional Machine Learning: Simple and Interpretable
  Techniques Are Competitive to Deep Learning for Sleep Scoring
Do Not Sleep on Traditional Machine Learning: Simple and Interpretable Techniques Are Competitive to Deep Learning for Sleep ScoringBiomedical Signal Processing and Control (BSPC), 2022
Jeroen Van Der Donckt
Jonas Van Der Donckt
Emiel Deprost
N. Vandenbussche
Michael Rademaker
Gilles Vandewiele
Sofie Van Hoecke
283
47
0
15 Jul 2022
Feature matching as improved transfer learning technique for wearable
  EEG
Feature matching as improved transfer learning technique for wearable EEGBiomedical Signal Processing and Control (BSPC), 2021
E. Heremans
Huy P Phan
A. Ansari
Pascal Borzée
B. Buyse
D. Testelmans
M. D. Vos
OOD
253
15
0
29 Dec 2021
Automatic Sleep Staging of EEG Signals: Recent Development, Challenges,
  and Future Directions
Automatic Sleep Staging of EEG Signals: Recent Development, Challenges, and Future DirectionsPhysiological Measurement (Physiol. Meas.), 2021
Huy P Phan
Kaare B. Mikkelsen
281
130
0
03 Nov 2021
Pediatric Automatic Sleep Staging: A comparative study of
  state-of-the-art deep learning methods
Pediatric Automatic Sleep Staging: A comparative study of state-of-the-art deep learning methodsIEEE Transactions on Biomedical Engineering (IEEE Trans. Biomed. Eng.), 2021
Huy P Phan
Alfred Mertins
M. Baumert
353
19
0
23 Aug 2021
Robust learning from corrupted EEG with dynamic spatial filtering
Robust learning from corrupted EEG with dynamic spatial filteringNeuroImage (NeuroImage), 2021
Hubert J. Banville
Sean U. N. Wood
Chris Aimone
Denis A. Engemann
Alexandre Gramfort
249
39
0
27 May 2021
SleepTransformer: Automatic Sleep Staging with Interpretability and
  Uncertainty Quantification
SleepTransformer: Automatic Sleep Staging with Interpretability and Uncertainty QuantificationIEEE Transactions on Biomedical Engineering (IEEE Trans. Biomed. Eng.), 2021
Huy P Phan
Kaare B. Mikkelsen
Oliver Y. Chén
P. Koch
Alfred Mertins
M. D. Vos
395
261
0
23 May 2021
Dreem Open Datasets: Multi-Scored Sleep Datasets to compare Human and
  Automated sleep staging
Dreem Open Datasets: Multi-Scored Sleep Datasets to compare Human and Automated sleep stagingIEEE transactions on neural systems and rehabilitation engineering (TNSRE), 2019
Antoine Guillot
F. Sauvet
E. During
Valentin Thorey
666
128
0
31 Oct 2019
U-Time: A Fully Convolutional Network for Time Series Segmentation
  Applied to Sleep Staging
U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep StagingNeural Information Processing Systems (NeurIPS), 2019
Mathias Perslev
M. Jensen
Kenny Erleben
P. Jennum
Christian Igel
AI4TS
376
312
0
24 Oct 2019
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