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12/20/2022
Deep Riemannian Networks for EEG Decoding
State-of-the-art performance in electroencephalography (EEG) decoding ta...
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09/19/2022
A Framework for Preserving Privacy and Cybersecurity in Brain-Computer Interfacing Applications
Brain-Computer Interfaces (BCIs) comprise a rapidly evolving field of te...
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01/14/2022
When less is more: Simplifying inputs aids neural network understanding
How do neural network image classifiers respond to simpler and simpler i...
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09/24/2021
Towards a Governance Framework for Brain Data
The increasing availability of brain data within and outside the biomedi...
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06/18/2020
Understanding Anomaly Detection with Deep Invertible Networks through Hierarchies of Distributions and Features
Deep generative networks trained via maximum likelihood on a natural ima...
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02/11/2020
Machine-Learning-Based Diagnostics of EEG Pathology
Machine learning (ML) methods have the potential to automate clinical EE...
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08/14/2019
A Research Framework for Virtual Reality Neurosurgery Based on Open-Source Tools
Fully immersive virtual reality (VR) has the potential to improve neuros...
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07/17/2019
Deep Invertible Networks for EEG-based brain-signal decoding
In this manuscript, we investigate deep invertible networks for EEG-base...
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07/04/2018
The role of robot design in decoding error-related information from EEG signals of a human observer
For utilization of robotic assistive devices in everyday life, means for...
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06/20/2018
Cross-paradigm pretraining of convolutional networks improves intracranial EEG decoding
When it comes to the classification of brain signals in real-life applic...
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06/18/2018
A large-scale evaluation framework for EEG deep learning architectures
EEG is the most common signal source for noninvasive BCI applications. F...
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06/18/2018
A framework for large-scale evaluation of deep learning for EEG
EEG is the most common signal source for noninvasive BCI applications. F...
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06/05/2018
EEG-GAN: Generative adversarial networks for electroencephalograhic (EEG) brain signals
Generative adversarial networks (GANs) are recently highly successful in...
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06/05/2018
Generative Reversible Networks
Generative models with an encoding component such as autoencoders curren...
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06/05/2018
Training Generative Reversible Networks
Generative models with an encoding component such as autoencoders curren...
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05/04/2018
Intracranial Error Detection via Deep Learning
Deep learning techniques have revolutionized the field of machine learni...
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11/21/2017
Hierarchical internal representation of spectral features in deep convolutional networks trained for EEG decoding
Recently, there is increasing interest and research on the interpretabil...
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11/16/2017
The signature of robot action success in EEG signals of a human observer: Decoding and visualization using deep convolutional neural networks
The importance of robotic assistive devices grows in our work and everyd...
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10/25/2017
Deep Transfer Learning for Error Decoding from Non-Invasive EEG
We recorded high-density EEG in a flanker task experiment (31 subjects) ...
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08/26/2017
Deep learning with convolutional neural networks for decoding and visualization of EEG pathology
We apply convolutional neural networks (ConvNets) to the task of disting...
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08/04/2017
Brain Responses During Robot-Error Observation
Brain-controlled robots are a promising new type of assistive device for...
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07/20/2017
Acting Thoughts: Towards a Mobile Robotic Service Assistant for Users with Limited Communication Skills
As autonomous service robots become more affordable and thus available a...
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03/15/2017
Deep learning with convolutional neural networks for EEG decoding and visualization
A revised version of this article is now available at Human Brain Mappin...
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12/15/2015
Causal and anti-causal learning in pattern recognition for neuroimaging
Pattern recognition in neuroimaging distinguishes between two types of m...
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12/14/2015
Decoding index finger position from EEG using random forests
While invasively recorded brain activity is known to provide detailed in...
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11/15/2015
