Using Deep Networks for Scientific Discovery in Physiological Signals
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Uri Shalit | Danny Eytan | Tom Beer | Bar Eini-Porat | Sebastian Goodfellow | Uri Shalit | D. Eytan | S. Goodfellow | Bar Eini-Porat | Tom Beer
[1] Jieyu Zhao,et al. Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations , 2018, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[2] Uri Shalit,et al. Robust learning with the Hilbert-Schmidt independence criterion , 2019, ICML.
[3] Bernhard Schölkopf,et al. Measuring Statistical Dependence with Hilbert-Schmidt Norms , 2005, ALT.
[4] Yong Jae Lee,et al. Don’t Judge an Object by Its Context: Learning to Overcome Contextual Bias , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[5] Madalena Costa,et al. Multiscale entropy analysis of biological signals. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.
[6] Danny Eytan,et al. Atrial fibrillation classification using step-by-step machine learning , 2018 .
[7] Heiga Zen,et al. WaveNet: A Generative Model for Raw Audio , 2016, SSW.
[8] Danny Eytan,et al. Towards Understanding ECG Rhythm Classification Using Convolutional Neural Networks and Attention Mappings , 2018, MLHC.
[9] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[10] Jerome M. Siegel,et al. Sleep viewed as a state of adaptive inactivity , 2009, Nature Reviews Neuroscience.
[11] Anna Goldenberg,et al. What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use , 2019, MLHC.
[12] Stefan Carlsson,et al. CNN Features Off-the-Shelf: An Astounding Baseline for Recognition , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops.
[13] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[14] Tiago H. Falk,et al. Deep learning-based electroencephalography analysis: a systematic review , 2019, Journal of neural engineering.
[15] Gilles Vandewalle,et al. Sleep slow wave changes during the middle years of life , 2011, The European journal of neuroscience.
[16] Gal Chechik,et al. A causal view of compositional zero-shot recognition , 2020, NeurIPS.
[17] Eliyahu Kiperwasser,et al. Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations , 2016, TACL.
[18] Bernhard Schölkopf,et al. Regression by dependence minimization and its application to causal inference in additive noise models , 2009, ICML '09.
[19] Miad Faezipour,et al. Sleep Stage Classification Using EEG Signal Analysis: A Comprehensive Survey and New Investigation , 2016, Entropy.
[20] Sean L. Hill,et al. The Sleep Slow Oscillation as a Traveling Wave , 2004, The Journal of Neuroscience.
[21] S. Quan,et al. Recommended Amount of Sleep for Pediatric Populations: A Consensus Statement of the American Academy of Sleep Medicine. , 2016, Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine.
[22] A. Chesson,et al. The American Academy of Sleep Medicine (AASM) Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications , 2007 .
[23] Giovanni Calcagnini,et al. P-wave Variability and Atrial Fibrillation , 2016, Scientific Reports.
[24] François Laviolette,et al. Domain-Adversarial Training of Neural Networks , 2015, J. Mach. Learn. Res..
[25] Bolei Zhou,et al. Learning Deep Features for Discriminative Localization , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[26] Isaac Fernández-Varela,et al. A Convolutional Network for the Classification of Sleep Stages , 2018, Proceedings.
[27] Junmo Kim,et al. Learning Not to Learn: Training Deep Neural Networks With Biased Data , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[28] J. Samet,et al. The Sleep Heart Health Study: design, rationale, and methods. , 1997, Sleep.
[29] Andre Esteva,et al. A guide to deep learning in healthcare , 2019, Nature Medicine.
[30] Yoav Goldberg,et al. Adversarial Removal of Demographic Attributes from Text Data , 2018, EMNLP.
[31] Qiao Li,et al. AF classification from a short single lead ECG recording: The PhysioNet/computing in cardiology challenge 2017 , 2017, 2017 Computing in Cardiology (CinC).
[32] Andrew Y. Ng,et al. CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning , 2017, ArXiv.
[33] A. Chesson,et al. The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology, and Techinical Specifications , 2007 .
[34] Amjed S. Al-Fahoum,et al. Methods of EEG Signal Features Extraction Using Linear Analysis in Frequency and Time-Frequency Domains , 2014, ISRN neuroscience.