Interpretable Deep Neural Networks for Single-Trial EEG Classification

27 April 2016

Papers citing "Interpretable Deep Neural Networks for Single-Trial EEG Classification"

50 / 57 papers shown

Title
Deep comparisons of Neural Networks from the EEGNet family C. Köllod A. Adolf G. Márton I. Ulbert OOD 23 20 0 17 Feb 2023
FATE in AI: Towards Algorithmic Inclusivity and Accessibility Isa Inuwa-Dutse 58 9 0 03 Jan 2023
Disentangled Explanations of Neural Network Predictions by Finding Relevant Subspaces Pattarawat Chormai J. Herrmann Klaus-Robert Muller G. Montavon FAtt 120 20 0 30 Dec 2022
Deep Learning for Size and Microscope Feature Extraction and Classification in Oral Cancer: Enhanced Convolution Neural Network Prakrit Joshi O. H. Alsadoon Abeer Alsadoon Nada AlSallami Tarik Ahmed Rashid P. Prasad Sami Haddad 24 7 0 06 Aug 2022
Core-set Selection Using Metrics-based Explanations (CSUME) for multiclass ECG Sagnik Dakshit B. M. Maweu Sristi Dakshit Balakrishnan Prabhakaran 13 5 0 28 May 2022
A Simple Self-Supervised ECG Representation Learning Method via Manipulated Temporal-Spatial Reverse Detection Wen-Rang Zhang Shijia Geng linda Qiao 60 29 0 25 Feb 2022
Interpretable Convolutional Neural Networks for Subject-Independent Motor Imagery Classification Ji-Seon Bang Seong-Whan Lee 21 7 0 14 Dec 2021
Explainability: Relevance based Dynamic Deep Learning Algorithm for Fault Detection and Diagnosis in Chemical Processes P. Agarwal Melih Tamer H. Budman AAML 47 44 0 22 Mar 2021
Interpretable Deep Learning for the Remote Characterisation of Ambulation in Multiple Sclerosis using Smartphones Andrew P. Creagh F. Lipsmeier M. Lindemann M. D. Vos 105 17 0 16 Mar 2021
Interpreting Deep Learning Models for Epileptic Seizure Detection on EEG signals Valentin Gabeff T. Teijeiro Marina Zapater L. Cammoun S. Rheims P. Ryvlin David Atienza Alonso 38 59 0 22 Dec 2020
GANterfactual - Counterfactual Explanations for Medical Non-Experts using Generative Adversarial Learning Silvan Mertes Tobias Huber Katharina Weitz Alexander Heimerl Elisabeth André GAN AAML MedIm 104 74 0 22 Dec 2020
Towards Robust Explanations for Deep Neural Networks Ann-Kathrin Dombrowski Christopher J. Anders K. Müller Pan Kessel FAtt 90 64 0 18 Dec 2020
It's All in the Name: A Character Based Approach To Infer Religion Rochana Chaturvedi Sugat Chaturvedi 65 23 0 27 Oct 2020
Understanding Information Processing in Human Brain by Interpreting Machine Learning Models Ilya Kuzovkin HAI 24 2 0 17 Oct 2020
Staging Epileptogenesis with Deep Neural Networks D. Lu S. Bauer V. Neubert L. Costard F. Rosenow Jochen Triesch 34 6 0 17 Jun 2020
OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold Mohamed Yousef Tom E. Bishop AI4TS 94 82 0 12 Jun 2020
Explainable Artificial Intelligence: a Systematic Review Giulia Vilone Luca Longo XAI 110 271 0 29 May 2020
Sequential Interpretability: Methods, Applications, and Future Direction for Understanding Deep Learning Models in the Context of Sequential Data B. Shickel Parisa Rashidi AI4TS 61 17 0 27 Apr 2020
MetaSleepLearner: A Pilot Study on Fast Adaptation of Bio-signals-Based Sleep Stage Classifier to New Individual Subject Using Meta-Learning Nannapas Banluesombatkul Pichayoot Ouppaphan Pitshaporn Leelaarporn Payongkit Lakhan Busarakum Chaitusaney ... Ekapol Chuangsuwanich Wei Chen Huy Phan Nat Dilokthanakul Theerawit Wilaiprasitporn 90 1 0 08 Apr 2020
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications Wojciech Samek G. Montavon Sebastian Lapuschkin Christopher J. Anders K. Müller XAI 141 83 0 17 Mar 2020
Machine-Learning-Based Diagnostics of EEG Pathology Lukas A. W. Gemein R. Schirrmeister P. Chrabaszcz Daniel Wilson Joschka Boedecker A. Schulze-Bonhage Frank Hutter T. Ball 81 159 0 11 Feb 2020
On Interpretability of Artificial Neural Networks: A Survey Fenglei Fan Jinjun Xiong Mengzhou Li Ge Wang AAML AI4CE 94 317 0 08 Jan 2020
When Explanations Lie: Why Many Modified BP Attributions Fail Leon Sixt Maximilian Granz Tim Landgraf BDL FAtt XAI 88 132 0 20 Dec 2019
Self Organizing Nebulous Growths for Robust and Incremental Data Visualization Damith A. Senanayake Wei Wang S. Naik Saman K. Halgamuge AI4TS 43 16 0 09 Dec 2019
Analysis of Explainers of Black Box Deep Neural Networks for Computer Vision: A Survey Vanessa Buhrmester David Münch Michael Arens MLAU FaML XAI AAML 112 367 0 27 Nov 2019
Towards Best Practice in Explaining Neural Network Decisions with LRP M. Kohlbrenner Alexander Bauer Shinichi Nakajima Alexander Binder Wojciech Samek Sebastian Lapuschkin 103 150 0 22 Oct 2019
Towards Explainable Artificial Intelligence Wojciech Samek K. Müller XAI 87 449 0 26 Sep 2019
Explaining and Interpreting LSTMs L. Arras Jose A. Arjona-Medina Michael Widrich G. Montavon Michael Gillhofer K. Müller Sepp Hochreiter Wojciech Samek FAtt AI4TS 76 79 0 25 Sep 2019
Explaining Convolutional Neural Networks using Softmax Gradient Layer-wise Relevance Propagation Brian Kenji Iwana Ryohei Kuroki S. Uchida FAtt 72 98 0 06 Aug 2019
Robust and Resource Efficient Identification of Two Hidden Layer Neural Networks M. Fornasier T. Klock Michael Rauchensteiner 73 18 0 30 Jun 2019
A Survey on Deep Learning-based Non-Invasive Brain Signals:Recent Advances and New Frontiers Xiang Zhang Lina Yao Xianzhi Wang Jessica J. M. Monaghan David Mcalpine Yu Zhang 3DV 69 140 0 10 May 2019
NNVA: Neural Network Assisted Visual Analysis of Yeast Cell Polarization Simulation Subhashis Hazarika Haoyu Li Ko-Chih Wang Han-Wei Shen Ching-Shan Chou 91 20 0 19 Apr 2019
Deep learning in bioinformatics: introduction, application, and perspective in big data era Yu Li Chao Huang Lizhong Ding Zhongxiao Li Yijie Pan Xin Gao AI4CE 96 302 0 28 Feb 2019
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn Sebastian Lapuschkin S. Wäldchen Alexander Binder G. Montavon Wojciech Samek K. Müller 106 1,022 0 26 Feb 2019
Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI Shane T. Mueller R. Hoffman W. Clancey Abigail Emrey Gary Klein XAI 76 285 0 05 Feb 2019
Deep learning-based electroencephalography analysis: a systematic review Yannick Roy Hubert J. Banville Isabela Albuquerque Alexandre Gramfort T. Falk J. Faubert 144 976 0 16 Jan 2019
A General End-to-end Diagnosis Framework for Manufacturing Systems Ye Yuan Guijun Ma Cheng Cheng Beitong Zhou Huan Zhao Hai-Tao Zhang Han Ding AI4CE 75 122 0 17 Dec 2018
Analyzing Neuroimaging Data Through Recurrent Deep Learning Models A. Thomas H. Heekeren K. Müller Wojciech Samek 63 78 0 23 Oct 2018
Explaining the Unique Nature of Individual Gait Patterns with Deep Learning Fabian Horst Sebastian Lapuschkin Wojciech Samek K. Müller W. Schöllhorn AI4CE 63 213 0 13 Aug 2018
AudioMNIST: Exploring Explainable Artificial Intelligence for Audio Analysis on a Simple Benchmark Sören Becker Johanna Vielhaben M. Ackermann Klaus-Robert Muller Sebastian Lapuschkin Wojciech Samek XAI 113 100 0 09 Jul 2018
EEG-GAN: Generative adversarial networks for electroencephalograhic (EEG) brain signals K. Hartmann R. Schirrmeister T. Ball GAN AI4TS 80 235 0 05 Jun 2018
Compact and Computationally Efficient Representation of Deep Neural Networks Simon Wiedemann K. Müller Wojciech Samek MQ 87 71 0 27 May 2018
Towards Explaining Anomalies: A Deep Taylor Decomposition of One-Class Models Jacob R. Kauffmann K. Müller G. Montavon DRL 74 97 0 16 May 2018
Compact Convolutional Neural Networks for Classification of Asynchronous Steady-state Visual Evoked Potentials Nicholas R. Waytowich Vernon J. Lawhern J. Garcia J. Cummings J. Faller P. Sajda J. Vettel 70 187 0 12 Mar 2018
Bioinformatics and Medicine in the Era of Deep Learning D. Bacciu P. Lisboa José D. Martín R. Stoean A. Vellido AI4CE BDL 64 17 0 27 Feb 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 181 4,007 0 06 Feb 2018
Hierarchical internal representation of spectral features in deep convolutional networks trained for EEG decoding K. Hartmann R. Schirrmeister T. Ball 87 27 0 21 Nov 2017
Applications of Deep Learning and Reinforcement Learning to Biological Data M. S. M. Mahmud M. S. Kaiser Amir Hussain S. Vassanelli OffRL AI4CE 85 646 0 10 Nov 2017
Deep Transfer Learning for Error Decoding from Non-Invasive EEG M. Völker R. Schirrmeister L. Fiederer Wolfram Burgard T. Ball 101 37 0 25 Oct 2017
Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges Muhammad Usama Junaid Qadir Aunn Raza Hunain Arif K. Yau Y. Elkhatib Amir Hussain Ala I. Al-Fuqaha SSL 91 330 0 19 Sep 2017