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Multivariate biosignals are prevalent in many medical domains, such as electroencephalography, polysomnography, and electrocardiography.
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Human EEG shows long-range temporal correlations of oscillation amplitude in theta, alpha and beta bands across a wide age range
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Christoph M Michel and Micah M Murray · 2012
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How to learn a graph from smooth signals
Vassilis Kalofolias · 2016
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Geometric deep learning: Going beyond euclidean data
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An open access database for evaluating the algorithms of electrocardiogram rhythm and morphology abnormality detection
Feifei Liu, Chengyu Liu, Lina Zhao, Xiangyu Zhang, Xiaoling Wu, Xiaoyan Xu, Yulin Liu, Caiyun Ma, Shoushui Wei, Zhiqiang He, Jianqing Li, and Eddie Ng Yin Kwee · 2018
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Antonio Ortega, Pascal Frossard, Jelena Kovačević, José M F Moura, and Pierre Vandergheynst · 2018
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Clinical use of a home sleep apnea test: An updated american academy of sleep medicine position statement
Ilene M Rosen, Douglas B Kirsch, Kelly A Carden, Raman K Malhotra, Kannan Ramar, R Nisha Aurora, David A Kristo, Jennifer L Martin, Eric J Olson, Carol L Rosen, James A Rowley, Anita V Shelgikar, and American Academy of Sleep Medicine Board of Directors · 2018
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Structured sequence modeling with graph convolutional recurrent networks
Youngjoo Seo, Michaël Defferrard, Pierre Vandergheynst, and Xavier Bresson · 2018
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The Temple University Hospital Seizure Detection Corpus
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Rewon Child, Scott Gray, Alec Radford, and Ilya Sutskever · 2019
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Temporal graph convolutional networks for automatic seizure detection
Ian C Covert, Balu Krishnan, Imad Najm, Jiening Zhan, Matthew Shore, John Hixson, and Ming Jack Po · 2019
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Bag of tricks for image classification with convolutional neural networks
Tong He, Zhi Zhang, Hang Zhang, Zhongyue Zhang, Junyuan Xie, and Mu Li · 2019
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Spatio-Temporal graph structure learning for traffic forecasting
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GNNGuard: Defending graph neural networks against adversarial attacks
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Rethinking attention with performers
Krzysztof Marcin Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Quincy Davis, Afroz Mohiuddin, Lukasz Kaiser, David Benjamin Belanger, Lucy J Colwell, and Adrian Weller · 2021
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Dynamic adaptive Spatio-Temporal graph convolution for fMRI modelling
Ahmed El-Gazzar, Rajat Mani Thomas, and Guido van Wingen · 2021
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Lipschitz recurrent neural networks
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Decoupled weight decay regularization
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Overview of EEG, electrode placement, and montages
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Graph wavenet for deep spatial-temporal graph modeling
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How powerful are graph neural networks?
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Neural memory networks for seizure type classification
David Ahmedt-Aristizabal, Tharindu Fernando, Simon Denman, Lars Petersson, Matthew J Aburn, and Clinton Fookes · 2020
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Adaptive graph convolutional recurrent network for traffic forecasting
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Combining recurrent, convolutional, and continuous-time models with linear state space layers
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Transfer graph neural networks for pandemic forecasting
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Discrete graph structure learning for forecasting multiple time series
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Epileptic seizures detection using deep learning techniques: A review
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A survey on graph structure learning: Progress and opportunities
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