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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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07/16/2022
On the Importance of Hyperparameters and Data Augmentation for Self-Supervised Learning
Self-Supervised Learning (SSL) has become a very active area of Deep Lea...
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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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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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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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06/05/2018
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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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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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
